Conference Agenda

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Session Overview
21-PM1-04: ST9.1 - Marketing and Innovation
Friday, 21/June/2019:
1:00pm - 2:30pm

Session Chair: Aurelie HEMONNET, Aix Marseille University
Session Chair: Emmanuelle Le Nagard, ESSEC Business School
Location: Amphi Grégory

Session Abstract

Innovation is a major issue in companies and more broadly organizations, all the more as the failure rates of new products and services remain structurally important. Traditional marketing techniques often prove to be ineffective for the design and diffusion of truly innovative offers, hence the need for a real "innovation marketing". In this context, this track seeks to gather contributions on concepts and methods that would help organizations to better understand and overcome this difficulty. Topics that can be addressed include :

- Role of the marketing function in organizations for the design of innovative offers, in relation with other functions (R & D, design, production, sales ...)

- Design of user innovation according to their profiles (lead-users, late adopters,…) and the method (co-creation, innovation contests, crowdsourcing).

- Adoption of innovations by customers and users: consumer behavior in the face of innovations, learning difficulties, perceived value and risk of innovation.

- Diffusion of innovations: diffusion model, sales forecast, role of opinion leaders, ...

- Launch strategy: orchestration of the launch in time, role of the distribution, pace of launch of the various innovations, ...

- Role of brands in innovation: strategic role in innovation, role in the launch and adoption of innovation, influence on the perception and attitude of customers to innovation, ...

These themes are of course not exhaustive, and other contributions relating marketing themes to that of innovation will be considered.

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Helping students to succeed with technology, a Mobile Coaching App across Cultures: a comparison between France and Mexico.

Niousha shahidi1, Silvia Cacho-Elizondo2, Vesselina Tossan3

1EDC PARIS BUSINESS SCHOOL, France; 2IPADE Business School, Mexico; 3Conservatoire National des Arts et Métiers, EDC PARIS BUSINESS SCHOOL, France


Mobile apps for e-coaching have been developed worldwide. Currently, higher education can be difficult. Students require personal and professional advice. This advice is usually provided by faculty, administrative staff, or peers. However, mobile technology could provide an innovative coaching based on virtual and digital features and enhancing students learning experience.


In past decades, a variety of theoretical perspectives have been developed to address adoption of IT innovations. One of the most widely used models is the TAM, which was originally proposed by Davis et al. (1992). Hong and Tam (2006) further developed this model to obtain the MIAAM by focusing on four sets of adoption drivers: 1) General technology perceptions, 2) Technology-specific perceptions, 3) User psychographics and 4) Social influence and demographics. Various authors have already used the TAM in studies comparing different countries (Ashraf et al., 2014; Dinev et al. , 2009; Li et al., 2009). Culturally, Mexico and France share common and different traits (Hofstede, 1993).

Literature Gap

To the best of our knowledge, this study constitutes a first step in the comparison of mobile coaching app adoption patterns across different countries. Mexico and France are selected in this work because they share common patterns, but also differ with regard to their politics, economies, cultures, and legal regulations.

Research Questions

This paper assesses the adoption of a mobile coaching app that could encourage students via a technology-based platform, with the aim of comparing the antecedents explaining adoption patterns in Mexican and French contexts. We consider a model inspired by the Technology Acceptance Model and the Multipurpose Information Appliances Adoption Model.


This study compares Mexico and France based on a model inspired by the TAM proposed by Davis (1989) and also, by the MIAAM developed by Hong and Tam (2006). The same survey was administered to both French and Mexican students. The objective was to validate the adoption model for a mobile coaching app in these two countries, with identification of similarities and differences.

First, the authors studied the reliability and validity of the scales to assess the measurement instruments used to test the constructs. Then, the multi-group structural equation modelling approach is used to test the proposed model’s causal structure.

Empirical Material

A survey was conducted to collect data among higher education students enrolled in business schools in Mexico and France. The data collected was used to test the theoretical model. The questionnaire, which was originally in English, was translated into French and Spanish and double-checked by the authors. Questionnaires were designed to be self-administered and were placed online. The survey remained available for 20 days, respondents could answer it in 10 to 15 minutes.

The samples were composed of 186 Mexican students and 194 French students, who answered the survey in Spanish and French, respectively. Most interviewees were mainly from highest-ranked business schools, with some coming from public universities. Note that the participants received an email inviting them to participate in the study.

Given the theoretical framework, six key adoption levers were identified: Behavioural Intention, Perceived Usefulness, Perceived Ease of Use, Social Influence, Perceived Enjoyment, Perceived Monetary Value. Six Likert-type scales with six items ranging from ‘strongly disagree’ to ‘strongly agree’ were used to test our model’s variables.


On average, all six variables (Intention, Perceived Usefulness, Social Influence, Perceived Enjoyment, Perceived Monetary Value) of the tested model differed significantly between the Mexican and French samples (except Perceived ease of use).

For both countries, the model was partially validated for the adoption of a mobile coaching app to support students. It was found that Perceived Ease of Use influences Perceived Usefulness, which in turn influences the Intention to adopt the mobile coaching app. However, Perceived Enjoyment, Social Influence, and Perceived Ease of Use do not directly influence the Intention. Social Influence directly affects Perceived Usefulness. Perceived Ease of Use and Social Influence, both have an indirect effect on Intention through Perceived Usefulness.

According to the results, a significant difference was observed in the relationship between Perceived Ease of Use and Perceived Usefulness.

Contribution to Scholarship

This study contributes to the literature by building on previous knowledge of consumer decision-making and technology adoption patterns in educational contexts across countries. Future research is still needed to improve the generalization of findings, especially if an app is actually developed and the current framework is applied across other mobile services.

The TAM and the MIAAM have been shown to be widely applicable to various technological innovation adoption processes (in different countries) and will likely continue to be applied broadly and globally.

Mexico with a high Power Distance profile validates the adoption model (McCoy, et al., 2007).

Contribution to Practice

The findings encourage young adults’ acceptance of mobile coaching apps to better organize their studies, highlighting convenience benefits, are relevant to companies offering these educational coaching services, which are increasingly digitalized, to better design innovative virtual counselling platforms. A reward system providing praise could also aid successful use of this service and render it engaging and compelling. The importance of social influence indicates that the benefits of this type of online counselling can spread through word of mouth, if the service is well designed and mutualized between several research institutes and schools.


This research deals with the adoption of an innovative coaching app for students exploring facilitators and barriers in the diffusion of this type of mobile services in educational contexts. Based on TAM and MIAAM models, we evaluated patterns in two cultural contexts (Mexico & France).

9.1“Adoption of innovations by users”


Al-Shantaf, S., Nguyen, M., Mathai, G. & Steinberg, H., 2017. Healthcare Management & Cultural Differences in France, Germany, India, Mexico, Saudi Arabia, & The USA. s.l., s.n., pp. 1-5.

Anderson, J. C. & Gerbing, D. W., 1988. Structural Equation Modeling in Practice: A Review and Recommended Two-step Approach. Psychological Bulletin, Volume 103, pp. 411-423.

Ashraf, A. R., Narongsak, T. & Seigyoung, A., 2014. The application of the Technology Acceptance Model Under Different Cultural Contexts: The Case of Online Shopping Adoption. Journal of International marketing, 22(3), pp. 68-93.

Bouzaabia, O., Bouzaabia, R. & Capatina, A., 2016. Determinants of Internet Use by Senior Generation: A Cross Cultural Study. International Journal of Technology and Human Interaction, 12(1), pp. 63-82.

Buschek, D., Hassib, M. & Alt, F., 2018. Personal Mobile Messaging in Context: Chat Augmentations for Expressiveness and Awareness. ACM Transactions on Computer-Huamn Interaction, 25(4), pp. 23:1-23:33.

Davis, F. D., 1989. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, Volume 13, pp. 319-340.

Davis, F. D., Bagozzi, R. P. & Warshaw, P. R., 1992. Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), pp. 1111-1132.

Dinev, T., Goo, J., Hu, Q. & Nam, K., 2009. User behavior towards protective information technologies: the role of national cultural differences. Info Systems Jo, pp. 391-412.

Dodds, W. B., Monroe, K. B. & Grewal, D., 1991. Effects of Price, Brand, and Store Information on Buyers’ Product Evaluations. Journal of Marketing Research, 28(3), pp. 307-319.

Geissler, H., Hasenbein, M., Kanatouri, S. & Wegener, R., 2014. E-coaching, Conceptual and Virtual Findings of a Virtual Coaching Programme. International Journal of Evidence Based Coaching and Mentoring, August.12(2).

Ghods, N., 2009. Distance coaching. The relationship between coach-client relationship, client satisfaction and coaching outcomes, Unpublished doctoral dissertation,. San Diego: s.n.

Hofstede, G., 1993. Cultural constraints in management theories. Academy of Management Executive, Volume 7, pp. 81-94.

Hofstede, G., Hofstede, G. J. & Minkov, M., 2010. Cultures et organisations comprendre nos programmations mentales. Paris: Pearson Education.

Hong, S. J. & Tam, K. Y., 2006. Understanding the Adoption of Multipurpose Information Appliances: The case of Mobile Data Services. Information Systems Research, 17(2), pp. 162-179.

Li, X., Hess, T. J., Mc Nab, A. L. & Yu, Y., 2009. Culture and Acceptance of Global Web Sites: A Cross-Country Study of the Effects of National Cultural Values on Acceptance of a Personal Web Portal. The Data Base for Advances in Information Systems, 4(4).

McCoy, S., Galletta, D. F. & King, W. R., 2007. Applying TAM across cultures: the need for caution. European Journal Of Information Systems, 16(1), pp. 81-90.

Straub, D., Keil, M. & Brenner, W., 1997. Testing the technology acceptance model across cultures: a three country study. Information & Management, Volume 33, pp. 1-11.


Touzani, M., Charfi, A. A., Boistel, P. & Niort, M.-C., 2017. Connecto ergo sum! An exploratory study of the motivations behind the usage of connected objects. Information & Management, Volume In Press.

Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D., 2003. User acceptance of Information Technology, Towards a Unified View. MIS Quarterly, 27(3), pp. 425-478.

“Don’t touch my meter!” When municipalities resist smart meters: linking argumentative strategies and levels of resistance

Cecile Chamaret1, Veronique Steyer1, Julie Mayer2

1i3-crg, Ecole polytechnique, IP Paris, France; 2Université Paris-Dauphine, PSL Research University, CNRS, UMR 7088, DRM, Management & Organisation, 75016 PARIS, FRANCE


Resistance is growing concerning the rollout of smart meters in France, challenging adoption of such innovation. Our research aims at understanding one specific level of resistance in the case of smart meters : cities.


Following the call of Gatignon & Robertson (1989) for specific studies on resistance apart from innovation adoption, Ram & Sheth (1989) have first conceptualized resistance to innovation and brought out the drivers of such behaviors. They identified functional barriers and psychological barriers. We also rely on risk perception to adress drivers of resistance and apply them to the specific case of smart meters. We link drivers of resistance to degrees of resistance. Previous research identified three different attitudes when resisting innovation: postponement, rejection and opposition (Szmigin and Foxall, 1998). Following Kleijnen et al. (2009), we consider that postponement is the decision of not adopting an innovation at a point in time, without this decision being irreversible. Rejection represents a “strong inclination not to adopt the innovation” (Rogers, 2003). Finally, when consumers don’t want the innovation and decide to fight against it, it results in opposition.

Literature Gap

Drivers of resistance have been studied for individuals. Case of resistance at macro levels are not studied.

Research Questions

What are the drivers and strategies of resistance to innovation at the level of municipalities in the case of French smart meters ?


To study the link between drivers and degrees of municipalities’ resistance to Linky meters, we performed a cluster analysis on the database. We run several clustering algorithms to examine the differences among municipalities along the dimensions previously described. We focused on Sneath and Sokal (1963)’s clustering algorithms, which extracted five clearly identifiable grouping. Each cluster has been assigned a generic name that reflects the overall characteristics of the grouping.

Empirical Material

The data collection relied on municipalities’ report of their decision to reject Linky. In France, municipalities’ resistance to electricity smart meters is characterized by the decision of 690 municipalities (i.e. more than 18%) to reject the installation of Linky meters. Reports of those sessions (including the nature of decision, number of votes, and the arguments to justify the decision) are public and published online. We collected reports published from April 2017 to May 2018.


The aim of our analysis was first to see if different argumentative strategies were followed by the French city councils expressing resistance towards the Linky smart meter roll-out. Our clusters analysis revealed five different clusters of municipalities, each resorting to a differentiating use of arguments to support its decision to resist to a certain extent to mandatory general roll-out of Linky on their territories.

We then were interested to see if different argumentative strategies were related to different levels of resistance to the Linky smart meter, revealed in the nature of the decision taken by the cities, that is from the lighter to the stronger degree: giving the choice to the individual citizens, postponing the roll-out on the totality of the municipality and opposing it.

Contribution to Scholarship

this research is another empirical case study of innovation resistance on a specific case of forced adoption. It helps to see which arguments urge the strongest forms of resistance. We challenge the results of Kleijnen et al. (2009) who link opposition to the perception of physical risks and a shaking of traditions and norms. In the case of French smart meters, the arguments linked to the property of the meter combined with the absence of perceived benefits, perceived macroeconomic and ethical risks and arguments defending that current meter function work perfectly are the arguments pushing for rejection. On the contrary, the combination of perceived health, functional, data risks and arguments liked to property pushes for the weakest form of resistance. It looks that municipalities using the only argument of property (and fighting for rejection) use the legal argument as a strategy to be the most efficient in their resistance.

Contribution to Practice

We highlight the need for a proactive differentiated communication within the process of implementation of smart meter, which encompass intermediary actors. Indeed, electric meters concern several stakeholders, including actors that play an intermediary role between implementors and their final users. As they play a role of trigger or obstacle to the implementation of smart meters, a specific communication strategy should be defined to board municipalities. This includes not only reassuring them toward the risks for electric meters’ users, but also to convincing them that this technology does not jeopardize with their particular objectives and responsibility.


This article deals with resistance to innovation with an ongoing case of rollout in France.


Balta-Ozkan, N., Davidson, R., Bicket, M., & Whitmarsh, L. (2013). Social barriers to the adoption of smart homes. Energy Policy, 63, 363-374.

Balta-Ozkan, N., Boteler, B., & Amerighi, O. (2014). European smart home market development: Public views on technical and economic aspects across the United Kingdom, Germany and Italy. Energy Research & Social Science, 3, 65-77.

Buchanan, K., Banks, N., Preston, I., & Russo, R. (2016). The British public’s perception of the UK smart metering initiative: Threats and opportunities. Energy Policy, 91, 87-97.

Chilvers, J., & Longhurst, N. (2016). Participation in transition (s): reconceiving public engagements in energy transitions as co-produced, emergent and diverse. Journal of Environmental Policy & Planning, 18(5), 585-607.

Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International journal of human-computer studies, 59(4), 451-474.

Ford, J. D., Ford, L. W., & D'Amelio, A. (2008). Resistance to change: The rest of the story. Academy of management Review, 33(2), 362-377.

Gatignon, H., & Robertson, T. S. (1989). Technology diffusion: an empirical test of competitive effects. The Journal of Marketing, 35-49.

Inderberg, T. H. (2015). Advanced metering policy development and influence structures: The case of Norway. Energy Policy, 81, 98-105.

Jacoby, J., & Kaplan, L. B. (1972). The components of perceived risk. ACR Special Volumes.

Jennings, M. G. (2013). A smarter plan? A policy comparison between Great Britain and Ireland's deployment strategies for rolling out new metering technologies. Energy policy, 57, 462-468.

Kaufmann, S., Künzel, K., & Loock, M. (2013). Customer value of smart metering: Explorative evidence from a choice-based conjoint study in Switzerland. Energy Policy, 53, 229-239.

Kleijnen, M., Lee, N., & Wetzels, M. (2009). An exploration of consumer resistance to innovation and its antecedents. Journal of economic psychology, 30(3), 344-357.

Krishnamurti, T., Schwartz, D., Davis, A., Fischhoff, B., de Bruin, W. B., Lave, L., & Wang, J. (2012). Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters. Energy Policy, 41, 790-797.

McHenry, M. P. (2013). Technical and governance considerations for advanced metering infrastructure/smart meters: Technology, security, uncertainty, costs, benefits, and risks. Energy Policy, 59, 834-842.

Oreg, S., Bartunek, J. M., Lee, G., & Do, B. (2018). An affect-based model of recipients’ responses to organizational change events. Academy of Management Review, 43(1), 65-86.

Pereira, G. I., Specht, J. M., Silva, P. P., & Madlener, R. (2018). Technology, business model, and market design adaptation toward smart electricity distribution: Insights for policy making. Energy Policy, 121, 426-440.

Ram, S., & Sheth, J. N. (1989). Consumer resistance to innovations: the marketing problem and its solutions. Journal of consumer marketing, 6(2), 5-14.

Rogers, E. M. (2003). The diffusion of innovation 5th edition.

Sneath, P. H., & Sokal, R. R. (1973). Numerical taxonomy. The principles and practice of numerical classification.

Sovacool, B. K., Burke, M., Baker, L., Kotikalapudi, C. K., & Wlokas, H. (2017). New frontiers and conceptual frameworks for energy justice. Energy Policy, 105, 677-691.

Szmigin, I., & Foxall, G. (1998). Three forms of innovation resistance: the case of retail payment methods. Technovation, 18(6-7), 459-468.

Thomas, R., Sargent, L. D., & Hardy, C. (2011). Managing organizational change: Negotiating meaning and power-resistance relations. Organization Science, 22(1), 22-41.

Wilson, C., Hargreaves, T., & Hauxwell-Baldwin, R. (2017). Benefits and risks of smart home technologies. Energy Policy, 103, 72-83.

Marketing of Co-Created Products: The information communicator matters

Lina Fogt Jacobsen1, Ana Alina Tudoran1, Marian Garcia2

1Aarhus University - MAPP Centre, DK; 2University of Kent - Kent Business School, UK


Increasing competitive pressures requires firms to develop differentiated consumer-driven business models delivering superior value (Mitchell and Coles, 2003). Product co-creation processes between companies and consumers positively contribute to internal creativity and innovativeness (Tynan et al., 2010) with the potential to influence product perceptions among general consumers (Schreier et al., 2012).


Consumers’ perceived product value (PPV) consists of four dimensions related to quality, price, social value and emotional value (Sweeney and Soutar, 2001). PPV is influenced by the information communicator based on trust. Trust is viewed as ‘confidence in’ and ‘willingness to rely’ on the other actor (Milne and Boza, 1999). Similarity between the product provider and the consumer increases trust (Coulter and Coulter, 2002). Endorsement literature distinguishes between fellow consumers and companies as information communicators with the former seen as more persuasive among general consumers (Bickart and Schindler, 2001).

Further, co-creation information has been documented to have a positive effect on the perception of products among general consumers depending on their familiarity with co-creation (Schreier et al., 2012).

Taken together, 1) co-creation information positively influences general consumers’ product perceptions, and 2) persuasiveness of information is based on trust and depends on the communicator and its similarity with the consumer.

Literature Gap

There is a lack of research on the role of the information communicator in shaping consumers’ PPV of co-created products. Whilst emerging research suggests a positive influence of co-creation information on PPV among general consumers, we need to understand the reasons behind this, and its influence on particular value dimensions.

Research Questions

This paper studies the role of co-creation information communicator in shaping the PPV among general consumers. The paper examines i) the influence of co-creation information communicated by a company vs. co-creating consumers on four dimensions of PPV, and ii) how this relationship is mediated by trust in the product developers.


The study is based on experimental data. The treatment variable was co-creation information communicator. The participants were assigned randomly to three experimental groups: no information (Group 0), co-creation information communicated by the company (Group 1), and co-creation information communicated by the co-creating consumers (Group 2).

All respondents were presented with the same product concept – a new food product to be introduced in the market - from a well-known food company.

Post-test control group design was implemented to compare the three conditions with respect to the dimensions of trust and PPV. Familiarity with co-creation was assessed as a control factor.

Empirical Material

An online experiment was conducted with 679 participants randomly selected in Denmark. The respondents were sampled through a market research agency to be representative of the Danish population based on gender, age, and geographical region. To control for their initial preferences, respondents were screened based on the relevance of the product as well as their profession. The participants were then randomly assigned to the three experimental groups.


When consumers lack familiarity with co-creation between companies and consumers, co-creation information communicated by the co-creating consumers leads to significantly higher (vs. control group) PPV due to increased trust in terms of honesty, benevolence and competences of the product developers (i.e. ‘the people behind the product’). These findings suggest that consumers’ perception of product quality, price, social value and emotional value can be positively influenced by marketing products as co-created. However, this is not the case when co-creation information is communicated by a company. Overall, we found that trust mediates the relationship between co-creation information communicated by the co-creating consumers and PPV, and the direction of this relationship is highly influenced by the consumers’ familiarity with the concept of co-creation.

Furthermore, when co-creation information is communicated by a company, subject to the consumers’ co-creation familiarity, the effect on the PPV is not statistically different from the control group. This reveals that the company as communicator of the co-creation information is less likely to affect the consumers’ PPV compared to co-creating consumers as communicators.

Contribution to Scholarship

This study contributes to the emerging co-creation literature by adding to the understanding on the marketing of co-created products. Whilst existing (but scarce) research indicates benefits in marketing products as co-created, our study suggests that who communicates this information matters. Theoretically, the study integrates multiple research perspectives: perceived value and endorsement research with co-creation research to explain why co-creating consumers (vs. companies) are more effective in communicating the co-creation message to general consumers. Finally, by distinguishing between four dimensions of PPV, we provide a deeper understanding of how these various aspects of value can be individually influenced by marketing products as co-created – depending on the communicator.

Contribution to Practice

Managers should consider the information communicator when using co-creation as a marketing tool for their products. In markets lacking familiarity with co-creation as an innovation process, the co-creating consumers should act as the information communicator. In other words, the company should be less visible in this communication. In this way, companies can positively influence consumers’ trust in the product developers, and increase their perceived product value on dimensions related to quality, price social value, and emotional value.


The study contributes to the main theme by focusing on the link between industry and society. More specifically, it addresses the intercept between marketing and innovation (Track 9.1), by focusing on how co-created innovations can be marketed in order to increase consumers’ PPV.


BICKART, B. & SCHINDLER, R. M. 2001. Internet Forums as Influential Sources of Customer Information. . Journal of Interactive Marketing, 15, 31-40.

COULTER, K. S. & COULTER, R. A. 2002. Determinanats of Trust in a Service Provider: The moderating role of length of relationship. Journal of Services Marketing, 16, 35-50.

MILNE, G. R. & BOZA, M. E. 1999. Trust and Concern in Consumers' Perception of Marketing Information Management Practices. . Journal of Interactive Marketing, 13, 5-24.

MITCHELL, D. & COLES, C. 2003. The Ultimate Competitive Advantage of Continuing Business Model Innovation. Journal of Business Strategy, 24, 15-21.

SCHREIER, M., FUCHS, C. & DAHL, D. W. 2012. The Innovation Effect of User Design: Exploring consumers' innovation perceptions of firms selling products designed by users. Journal of Marketing, 76, 18-32.

SWEENEY, J. C. & SOUTAR, G. N. 2001. Consumer Perceived Value: The development of a multiple item scale. Journal of Retailing, 77, 203-220.


Who are the adopters of eco-friendly innovations? – A configurational analysis of consumers’ intention to purchase vegan meat substitutes

Laura Schilmeier, Fabian Reck

University of Bamberg, Germany


As environmental issues increasingly affect individuals, organizations, and societies, eco-friendly innovations such as vegan meat substitutes gain importance in management research and practice. Thereby, it has been shown that eco-friendly innovations often fail when it comes to successful market diffusion due to struggles in reaching a critical mass of adopters.


Due to its key role in innovation diffusion, consumer adoption of innovative products in general and eco-friendly innovations in specific has received considerable attention in management and marketing literature (Rogers, 2003). While early research mostly examined the effects of sociodemographics (e.g. Martinez et al., 1998), newer works criticize the relatively low explanatory power of these variables and argue that values, beliefs, and personal norms need to be accounted for as well (Wang et al., 2008). These considerations resulted in the value-belief-norm (VBN) theory (Stern, 2000). In the context of eco-friendly innovations, this theory has been used to explain the effects of personal values such as the new ecological paradigm (NEP) (e.g. Jansson et al., 2011) or hedonism (e.g. Heidenreich et al., 2017) as well as of personality traits such as the Big Five (Fraj & Martinez, 2006).

Literature Gap

Though research has observed a variety of factors influencing adoption behaviour, most literature takes a reductionistic perspective by only investigating isolated effects of single variables while neglecting complex causal interactions. Consequently, there is a lack of understanding on how the overall configuration of individuals’ values and traits affects adoption behaviour.

Research Questions

Addressing this research gap, this paper takes a configurational perspective (Fiss, 2011; Ragin, 2008) in order to uncover the overall archetypical “profiles” that characterize adopters of vegan meat substitutes. We aim to answer the following research question: Which configurations of sociodemographics, values, and personality traits predict adoptive behaviour?


We aim to achieve our research goals by taking a large-N fuzzy-set qualitative comparative analysis (fsQCA) approach. In a nutshell, fsQCA categorizes all observed research cases based on their combination of explanatory variables, extracts configurations that consistently lead to an outcome of interest and uses Boolean algebra to filter out overlaps and counterfactuals so that the most parsimonious number of “profiles” leading to an outcome is obtained (Ragin, 2008). Our theoretical framework of explanatory variables that serves as input for fsQCA includes two sociodemographic variables (gender, level of education), two personal values (NEP, hedonism), and the Big Five personality traits.

Empirical Material

We obtained data by conducting a large-scale online survey. The survey was posted in various online forums as well as on homepages of supermarket chains and smaller grocery stores. In all, we obtained 276 completed questionnaires, the final sample includes a similar number of males and females as well as respondents from different ages, educational levels, and income groups. Except for the sociodemographic variables which were treated as manifest constructs and enquired directly, all research variables were treated as reflective constructs and were measured based on multiple items rated on a five-point Likert scale. We followed Wang et al. (2008) and operationalized adoption behaviour based on respondents’ intention to purchase vegan meat substitutes. The measurement scale comprised three items. NEP (4 items), hedonism (3 items), extraversion (3 items), openness to experience (3 items), conscientiousness (3 items), agreeableness (3 items), and neuroticism (3 items) were measured using existing multi-item scales from previous literature. Tests for common-method bias, scale reliability, convergent validity, and discriminant validity demonstrated the adequacy of our measurement approach. Confirmatory factor analysis in AMOS indicated high levels of fit between the measurement model and the obtained data.


Before the actual fsQCA, we tested all research variables for necessity, i.e. if the respective factor needs to be present for high levels of adoptive behaviour. We found that NEP is a necessary condition for a person to be an adopter of vegan meat substitutes. Adding to this finding, fsQCA unveiled five major configurations leading to high levels of adoptive behaviour. First, there is the “Fashionista”. This configuration depicts a highly educated male that is characterized by high levels of extraversion and either high levels of NEP, high hedonism, or both. Second, the “Eco Warrior” category encompasses highly educated males and females that combine high extraversion, low agreeableness, high neuroticism with NEP. Third, females with rather low levels of education, low levels of openness, but high levels of NEP and conscientiousness are likely to be adopters of vegan meat substitutes. We term this profile “Genuine Believer”. Fourth, highly educated females with high agreeableness, low extraversion, high neuroticism, high conscientiousness, and high NEP display high levels of adoptive behaviour. For this profile, we use the label “Responsible Introvert”. Finally, the “Poster Child”-profile depicts women with high levels of NEP, hedonism, extraversion, openness, conscientiousness, and agreeableness.

Contribution to Scholarship

In this paper, we extend the theoretical understanding of eco-friendly innovation adoption by conceptualizing our explanatory variables as bundles of distinct, but interdependent influence factors that explain adoptive behaviour conjointly rather than in isolation. The paper shifts the focus from the net effects of single variables to the combinatorial effects of overall configurations. As a result, our analysis indicates five adopter profiles that can serve as “causal recipes” (Ragin, 2008), i.e. distinct combinations of sociodemographics, personal values, and personality traits which exert conjunctural effects on adoptive behaviour. Moreover, we are able to demonstrate that adopters of eco-friendly innovations may be driven by different values and attitudes so that there is more than one type of adopter. Hence, our paper provides a more nuanced perspective on the causality behind adoptive behaviour compared to previous mostly variance-theoretic works that assume the existence of one-size-fits-all explanations for determining the likelihood of innovation adoption.

Contribution to Practice

Our research contributes to managerial practice in several important ways. We demonstrate that there are different types of adopters of eco-innovations and thus recommend firms to take a differentiated and segmented marketing approach for novel eco-friendly products. The identified profiles of adopters can serve to guide them in positioning their products and designing communication strategies that are tailored to meet the needs and motivations of the particular adopter type. In all, our findings may help companies develop a more nuanced understanding of consumers adoption behaviour, achieve a critical mass of adopters timelier, and thus accelerate the diffusion process of eco-innovations.


Our paper addresses the following issue stated in the call: “Adoption of innovations by customers and users: consumer behavior in the face of innovations, […]”. By providing a fresh perspective on adoptive behaviour and a relevant empirical context, we hope to make a valuable contribution to the theme track.


Fiss, P. C. 2011. “Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organization Research.” Academy of Management Journal 54 (2): 393-420.

Fraj, E., and E. Martinez. 2006. “Influence of Personality on Ecological Consumer Behavior.” Journal of Consumer Behavior 5 (3): 167-181.

Heidenreich, S., P. Spieth, and M. Petschnig. 2017. “Ready, Steady, Green: Examining the Effectiveness of External Policies to Enhance the Adoption of Eco‐friendly Innovations.” Journal of Product Innovation Management 34 (3): 343-359.

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