Article History
Received: 23 March 2018
Revised: 15 May 2018
Accepted: 5 June 2018
Abstract
The present paper aims to address a demand-side perspective of bioeconomy by laying emphasis on the digitalization of markets and, subsequently, on the consumption patterns at the macroeconomic scale. The imperative for a sustainable economic model corroborated with the advances in digital technologies usage have reconfigured consumers' approaches and expectations and availed new forms of consumer behavior. Among these, the development of consumer-based online communities and of the online intellectual capital have often come forth as an undertaking of empowered consumers pursuing knowledgebased consumption patterns. The quest for sustainable, bio-labeled products on the digital markets has cemented the formation of new social aggregations built on the similarity of interests, goals, values, expectations, preferences, etc., giving way to consistent communication and interaction flows among their members and engendering profound transformations in today's society. Acknowledging all these facts, the study investigates the influences of the online intellectual capital on the consumption patterns through the lens of bioeconomy. The focus is set on the bio products consumption in two European countries (i.e., Romania and Italy), relying on a sample of over 700 active online consumers. Processed via a structural equation modeling technique, the data indicated the existence of significant influences among the considered variables.
Keywords: intellectual capital (IC), online communities, consumption, bio products, bioeconomy, digitalization.
JEL Classification: D18, F12, F68.
Introduction
In this context of today's economy, the fundamental transformation of economic systems is often seen as a solution of last resort to stagnation given the fact that, in the current economic models, "prices faced by producers and consumers (...) do not reflect environmental and social costs adequately" (Le Blanc, 2011, p. 151). Thus, transformation processes advocated by various scholars (Bina, 2013; Mazzucato and Perez, 2014) and policy makers (i.e., the Green Economy Initiative GEI, launched by the United Nations Environment; the Sustainable Development Goals, launched by United Nations Development Program) alike are more than ever focusing on bioeconomy - as opposed to the lock-in in carbon-based technologies (Unruh, 2000) - and on its potential to boost competitiveness and innovation.
In line with the EU documents, bioeconomy could be defined as the "production of renewable biological resources (biomass) and their conversion to food, feed, bio-based products and bioenergy" (European Commission, 2005, 2012; Trigo et al., 2013). Its higher aim resides in improved human well-being and social equity, with a significant reduction of environmental risks and ecological scarcities (UN Environment, 2018). If supported by national policies and institutions, the trade opportunities created by bioeconomy can enhance economic growth while helping states achieve their sustainable development goals.
For these profound and essential transformations to happen, two important technological aspects become of topical importance, as Pyka (2017) highlights: 1. Digitalization, including the key technological advancements given by artificial intelligence, robots, and augmented reality, all the more so as, launched in May 2010, the digital agenda for Europe has been designed to help unleash Europe's economic potential by means of the sustainable economic and social benefits deriving from the implementation of the digital single market (European Commission, 2010); 2. The so-called "knowledge-based bioeconomy" which replaces - in many applications - oil-based by bio-based materials. According to the Research Directorate-General European Commission (2009), "bioeconomy" includes all industries and economic sectors that produce, manage and otherwise exploit biological resources (e.g. agriculture, food, forestry, fisheries, etc.).
Building of these conceptual keystones which integrate the dynamics of digitalization and the multifield knowledge-based bioeconomy, the current paper aims at discussing the influences of the online intellectual capital brought forward by the digital economy on online consumption patterns and the consumer behavior related to bio products. The embraced approach relies on three pillars, that is: a. a consumer-friendly digital single market is one of the key priorities of EU's 2010 Digital Agenda; b. the emergence of new forms of intellectual capital (i.e., online intellectual capital) reconfigures the logic of the digital economy and gives way to empowered consumers and to knowledge-based consumption patterns; c. the propensity towards the consumption of bio products contributes as a pivotal incentive to the development of a "bioeconomic model" from the demand-side level. It is in this particular point that the main paper contribution is objectivized in that most of the studies on bioeconomy start from the inputs of the bioeconomic processes, focusing less on the stakeholders' influence. Hence, shifting the focus towards the consumers' online communities (Forman et al., 2008; Zhao et al., 2013), which assume "social responsibility" (Hobart and Sendeck, 2016) in their approach to sustainability and bio products, catalyzes a multidimensional comprehension of the current bioeconomic model.
These aspects considered, the paper was structured as follows. Firstly, the theoretical background is developed, with a special focus on the digitalization of the in the digital economy and on the online intellectual capital availed by the online communities. Secondly, the research purpose, objectives, hypotheses and methodology are presented. Thirdly, after the introduction of the conceptual framework, the measurement and structural models are assessed as derived from a structural equation modeling technique. Finally, the results are reported and discussed in terms of overall implications, limitations and future avenues.
1.Literature review
1.1.The digitalization of consumption patterns
In the knowledge-based bioeconomy, a massive leap towards sustainability requires both the supply-side (i.e., companies, producers) and the demand-side (i.e., consumers) to identify and implement new coordination and adaptive capacities. From the demand-side perspective, household access to broadband has determined a boost in internet purchases - from 59% (EU-28 in 2012) to 68% (EU-28 in 2017) (Eurostat, 2018). This is indicative of the fact that today's economy is facing major challenges and the digitalization has become auspicious due to the easy and affordable access to an Internet connection in most parts of the world (Van Gorp, 2015). As reported by the World Bank (2016), 40% of the world's population had access to the Internet, the evolution of different technologies (mobile communications, digital platforms, big data, cloud computing and social media) dramatically altering the way people interact, buy and inform themselves about products and services (Maher et al., 2016).
The transformations of the digital markets call for a different approach as they spring with merely novel facets: they are very competitive (Andrei et al., 2017a, 2017b; Gazzola et al., 2017); they are dynamic and highly innovative (Maher et al., 2016); they are two-sided: both individuals and suppliers can use them to search for information, respectively for promoting their products; they offer access to big data about their subscribers and they can reduce costs as online environments give way to increasingly more and more transactions rather than the offline stores (Maher et al., 2016). For instance, according to Statista's Digital Market Outlook (2018), e-commerce revenue in Europe is expected to increase from approximately 282 billion U.S. dollars in 2016 to approximately 430 billion in 2021.
Rapidly, digital technologies are recrafting the extant markets (OECD, 2009), with an immediate expression of "always open", prone to respond quickly and provide information suitable for different types of users. In this front, OECD (2016) underlines the key developments brought forward by the massive digitalization of economy, respectively: nonmonetary transactions (i.e., consumers acquire "free" goods and services, at the exchange personal data on preferences, motivations and expectations), digital content (i.e., technical specifications sometimes prevent consumers from understanding their rights and obligations), active consumers (i.e., consumer-to-consumer transactions often account for the success or failure of a line of products and/or services), mobile devices (i.e., how information is presented and accessed is essential, the accent placed on design), security risks and payment protection (i.e., consumers data require dedicated awareness, safety mechanisms, and special regulations), unsafe products (i.e., the online environment is very permeable to unsafe/forbidden products and, thus, needs close supervision).
All these factors along with the digitization of products and processes have deeply changed the behavior and expectations of consumers (Halttunen, 2016), in the sense that they are now having much more possibilities to gather information regarding their planned purchases, to endorse, to recommend, to connect with peer consumers, etc. (Miklošík, 2015, p. 167). In what concerns the demand-side, consumers are now able to compare benefits and prices with unprecedented ease and accuracy (Thompson, 2003; Vătămănescu, Nistoreanu and Mitan, 2017). This leads to consumer empowerment which is not only dependent on confidence and knowledge, but also implies the openness and intention to play an active consumer role (Espejo and Dominici, 2017). As stated by the European Union (2011, p. 2), the "empowered consumers make optimal decisions by understanding their own preferences and the choices available to them".
In order to make optimal decisions, consumers often resort to shortcuts, the online environment providing them with less time-consuming undertakings: the ability to compare prices, to look for the best offer, to check online the sales and promotions, establish the quality-price ratio (European Union, 2011; Gazzola et al., 2017; Vătămănescu, Nistoreanu and Mitan, 2017). Researches have demonstrated that, in digital markets, consumers "often value quality and product features over low prices" (Maher et al., 2016, p. 2). Another characteristic of online consumers, especially for the young generation, is the preoccupation for sustainable consumption and products: they are taking into account the CO2 footprint, the pollution or health effects, the origins of the products (Sogari et al., 2017), but also "the impacts which that consumption may have on the factors of production, including workers and resources" (OECD, 2009, p. 7)
For a growing number of consumers, the actual consumption has set itself up as a "way of expressing status and identity" (Dominici et al., 2017) and many online consumers are paying attention to their peers' opinions on various products (OECD, 2008, 2009). There are also differences when it comes to age - old vs. young consumers - Baby Boomers, Millennials and Gen Z are acting differently in the online communities (Dabija et al., 2017; Dabija et al., 2018) and gender (women are more likely to buy sustainable products: ecolabeled products or organic food; they write reviews and they are responsible for 80% of the acquisitions within a family; on the other side, men are buying less articles, but the more expensive ones: homes, cars and electronics) (OECD, 2008).
Furthermore, the new generation of consumers - the Millennials - is looking for "sustainable products, not just socially responsible companies" and they are loyal to brands they can personally use to live sustainable lives (Mahler, 2016). Here, the Euromonitor International's (2017) Global Consumer Trends Survey found that 53% of all respondents thought they can "make a difference to the world through their choices and actions". They are looking for the greater good and they would choose to work and buy from o company which is eco-friendly and more responsible (Hobart and Sendeck, 2016), they will be seeking for products that are sustainable and long-lasting (Vătămănescu, Nistoreanu and Mitan, 2017; Lakatos et al., 2018).
Given the lack of perceived boundaries, consumers are liable to explore and cement this tendency towards sustainable processes and outcomes via online communities as they often prefer to interact online in order to test their buying assumptions (Zhao et al., 2013; Bharati et al., 2015), to read and write reviews, to influence other consumers' choices worldwide. In the XXIst century, new consumer expectations and demands emerge and deploy, influencing both the business orientation and the consumption patterns.
1.2.The rise of the online intellectual capital within consumer-based online communities
The massive and substantial digitalization of markets and the knowledge-based bioeconomy have turned the attention of many organizations from the functional production models to more flexible, creative and innovative ones, adapted so as to meet the expectations of the digital consumer. This is even more imperative when considering that these exigencies have been acknowledged not only by the business sector, but by the European institutions equally, in the context of bioeconomy strategies (European Commission, 2017). For example, the report on food systems approaches for 2030 comprises explicit references to online forums "hosting a facility for questions, networking and exchange on more sustainable production and consumption" (p. 5), to online platforms allowing "communities to get involved with the redistribution of food (...) to create 'bridges' and build on the collaborative potential of ICT networks" (p. 7). As a clear recommendation, the report posits that "In creating 'online bridges' between citizens, organizations and stakeholders, digital technologies may form the basis for some elements of future food-sharing systems" (European Commission, 2017, p. 4).
Going beyond context-driven approaches, it has become obvious that digital consumers get increasingly empowered through constant exchange of knowledge and acumen with similar peers within consumer-based online communities (Vătămănescu, Nistoreanu and Mitan, 2017). Hence, new forms of intellectual capital (IC) flourish and widely affirm their relevance in the context of the digital economy.
Despite lack of consensus over a generally accepted definition, the intellectual capital could be defined and operationalized as a dynamic assemblage of knowledge and knowing capabilities acquired, harnessed, leveraged, transferred, exchanged, diffused, converted, etc. able to generate a wide spectrum of competitive advantages in various fields (Subramaniam and Youndt, 2005; Bratianu, 2009; Vătămănescu et al., 2015, 2016). At this level, three main components of the IC have been consistently summarized by the extant body of literature, namely the human capital, structural capital and relational capital (Dean and Kretschmer, 2007; Sharabati et al., 2010; Herremans et al., 2011; Leitner et al., 2014). All these IC components are interrelated and linked (Still et al., 2013) as human capital does not exist isolated, but in interactive relationships, while the relational capital can manifest itself because people, possessing knowledge, skills, experience and attitude interact with others.
The great majority of studies in the field of IC underscored the organization-centric approach on the IC components, still some recent papers have availed a digital-based framework for the overall discussion (Vătămănescu et al., 2015; Vătămănescu et al., 2016; Vătămănescu, Andrei and Pînzaru, 2018). A brand-new construct was coined, namely the "network-based intellectual capital" defined as "an intricate configuration and consistent interaction among people, knowledge, information, expertise, competences, know-how within complex and dynamic online social networks" (Vătămănescu et al., 2016, p. 596). Giving credit to the study conducted by Vătămănescu et al. (2016), the "network-based intellectual capital" is genuinely illustrative of the relationship between the three dimensions of IC (i.e., human, structural and relational) and the digitalization dynamics. Its scope goes beyond the organizational borders and adopts the reality of new online social aggregations of individuals who affiliate to different online (web) communities of interest, practice, etc.
By embracing the framework of new "network capabilities" (Still, 2014), online communities are aggregations of individuals who share common interests, practices, hobbies, experiences, communicating and interacting primarily over the Internet. These affiliations bring together people, knowledge, information, ideas and opinions and they contribute to learning, development and collaboration (Soto-Acosta et al., 2014). As a specific facet of these aggregations, the consumer-based online communities are moulded round product or brand-related issues, gathering people with similar consumption interests, preferences and behaviors (Cheung et al., 2008; Brodie et al., 2013; Wirtz et al., 2013).
In this vein, the online human capital comes forward as individual-embodied knowledge, education, creativity, empowerment, experience, skills, agility, motivations, attitudes, behaviours, etc. (Tovstiga and Tulugurova, 2007; Cricelli et al., 2014; Vătămănescu et al., 2016). The accumulation of online human capital is only the first step in the process of community formation and development. Progressively, its members develop a sense of familiarity and social interconnectedness, by converging towards a shared purpose and interest and by actively contributing to creating trust and strong bonds within the community (Forman et al., 2008).
The consumer-based online communities favour communication, information sharing and "enables consumers to gather, compare, review and share information about goods and services, and fosters the development of new business models, some of which facilitate consumer-to-consumer transactions" (OECD, 2016, p. 8) As a result, new forms of online intellectual capital emerge, that is, the online structural capital (product-related storehouses of knowledge comprising reviews, comments, analyses, images and pictures, stories, specific experiences, etc.), respectively, the online relational capital (referring to consistent communication and interaction flows, networking, exchanges, etc.) (Vătămănescu et al., 2016).
From the consumer-based online communities perspective, all the IC components objectivize themselves via two important aspects: a message source (the initiator of the message, also known as the reviewer) with all the inherent characteristics (social, geographical, ethical, etc.) and the message content (what the initiator is writing, namely the review) which may have a positive or negative valence (Forman et al., 2008; Zhao et al., 2013). Both aspects are connected and important: the former for creating the bonds and the affiliation feelings presented above (as an objectivization of the online relational capital) and the latter as a content "manifesto" (an objectivization of the online structural capital) directly influencing online sales and purchasing decisions.
In this respect, studies showed that the reviews coming from community members with similar characteristics are more likely to be considered when buying (Forman et al., 2008) and, when it comes to buying experiential products (like books, movies and music) - the other members' reviews are valued more than the own personal experience of the reader (Zhao et al., 2013). The new generation of consumers considers feedback as an important tool, so they find useful to provide feedback about products and services, to write reviews about their experiences with the brand and its deliverables and they consider this a "social duty" (Hobart and Sendeck, 2016) as members of specialized online communities. Therefore, given the fact the information is now available and very easy to access online, consumers may integrate multiple sources of information when making their decisions.
2.Methodology
Starting from the theoretical aspects previously depicted, the current research aims to investigate the influences of the intellectual capital - as generated by a highly-digital environment - on the consumption of bio products. In this respect, three main research objectives were established: O1. to examine the relationship between digitalization and the development of the online intellectual capital; O2. to analyze the relationship between the online intellectual capital and the consumption of bio products (understood as an incentive of the bioeconomy from the demand side); O3. to appraise the relationships between digitalization and the consumption of bio products by means of the three components of the intellectual capital, namely human capital, structural capital and relational capital.
Based on these research objectives, 7 hypotheses were formulated, that is:
* H1: Digitalization has a significant influence on the development of online human capital.
* H2: Digitalization has a significant influence on the development of online structural capital.
* H3: Digitalization has a significant influence on the development of online relational capital.
* H4: The online human capital has a significant influence on the consumption of bio products.
* H5: The online structural capital has a significant influence on the consumption of bio products.
* H6: The online relational capital has a significant influence on the consumption of bio products.
* H7: Digitalization has a significant influence on the consumption of bio products by means of the online intellectual capital.
The research hypotheses were tested via a questionnaire applied to a sample of 708 online consumers (aged between 19 and 39, M=22.96, SD=5.2) from two European countries, namely Romania and Italy. The selection of the two countries was a result of convenience sampling supported by a partnership between two universities and the availability of the targeted subjects. The questionnaire was distributed online between 2 and 28 November 2017. In its final form, the research instrument comprised 27 items measuring five constructs, as follows: 1. Digitalization (understood as the highly-digital environment favored by the online space) comprises three items referring to the intensification of various online flows in today's economy; 2. Online human capital (understood as the development of online communities consisting of empowered consumers) contains eight items; 3. Online structural capital (understood as the generation of content by empowered consumers) includes two items; 4. Online relational capital (understood as the development of communication and interaction flows among empowered consumers) comprises three items; 5. Consumption of bio products (understood as an incentive of bioeconomy from the demand side) consists of four items referring to the online consumers' buying patterns. All the multi-item constructs were measured on a five-point Likert scale where 1 = Strongly disagree and 5 = Strongly agree. Along with the items falling into the five constructs, the questionnaire also included socio-demographic items (gender, age, residence, education level, income).
In order to properly process the data and to analyze the formulated hypotheses, a partial least squares equation modeling technique (PLS-SEM) was employed via SmartPLS version 3 software (Ringle, Wende and Becker, 2015). The choice for a variance-based technique was supported by its wide usage for explorative undertakings in the framework of social sciences.
3.Results and discussion
3.1. Measurement model assessment
The assessment of the measurement model encompassed the examination of three main quality criteria: the factor loadings, convergent validity and discriminant validity in line with the recommendations of the specialized body of literature (for convergent validity - Barclay, Higgins and Thompson, 1995; Yi and Davis, 2003; Henseler, Ringle and Sinkovics, 2009; for discriminant validity - Fornell and Larcker, 1981; Henseler, Ringle and Sarstedt, 2015).
In the first step of the analysis, the properties of the constructs were computed in order to scrutinize the values for convergent validity, as shown in table no. 1.
As observed in table above, the recommended thresholds for all the psychometric properties are complied with, respectively CR > 0.7, AVE > 0.5 and factor loadings > 0.65.
The second step of the analysis included the assessment of the discriminant validity in accordance with Fornell and Larcker's (1981) criterion - all the square root of AVE (diagonal entries) have higher values than the construct correlations (non-diagonal entries), as illustrated in table no 2.
The discriminant validity was also evaluated in relation to the Heterotrait-Monotrait Ratio (HTMT), all values ranging between 0.239 and 0.758, thus below the recommend threshold of 1 (Henseler, Ringle and Sarstedt, 2015).
The third step of the measurement model assessment consisted of the examination of the variance inflation factor (VIF) outputs on purpose to detect potential issues in terms of multicollinearity among the five constructs considered in the model. In line with Diamantopoulos and Siguaw's (2006) requirements, all the VIF values were covered by the array from 1.163 and 2.916, thus lower than 3.3.
3.2. Structural model assessment
Given that the basic requirements for the measurement model assessment were complied with, the analysis stepped forward to the evaluation of the structural relationships in the model. As depicted in the figure below (figure no. 1), the model accounts for almost 30% of the variance in Consumption of Bio Products (as the R square value illustrates).
In line with Hair et al.'s (2014), the structural model was assessed by means of the computation of R2, beta, T statistics and P values using a bootstrapping procedure with 5000 resamples. The corresponding results and the decisions on hypotheses testing are presented in table no. 3.
As previously summarized, six out of the seven hypotheses were supported in the context of the current research. In this respect, the investigation revealed that digitalization has significant positive influences on the development of online human capital (ß = 0.318, p < 0.001), structural capital (ß = 0.146, p < 0.01) and online relational capital (ß = 0.474, p < 0.001). These findings are consistent with prior research (Still, 2014; Vătămănescu et al., 2015, 2016; European Commission, 2017) stating the impact of digital transformations on the advent of new online forms of aggregations, comprising consumers with similar interests and goals, preferences and expectations who interact on a regular basis. The consumer-based online communities set themselves up as an agora for their empowered members who objectivize their opinions, attitudes, behaviors, overall knowledge and experience by means of product-related or brand-related comments, reviews, storytelling, shared expertise. As shown in table no. 3, the highest influence pertains to the online relational capital, a fact which implies that digitalization has prevailingly encouraged constant flows of communication and interaction among the members of the online communities regarding bio products. These results validate the premise advanced by Pyka (2017) according to which digitalization - promoted and supported via the Digital Agenda for Europe - contributes both directly and indirectly to the debate on hot societal and economic issues and, implicitly, to the development of the inherent conditions for the formation of online communities based on common interests. Consequently, the implications of this strategy are not only seen by means of the single digital market, but also by means of the social dimension which brings to the fore new forms of collaboration and coordinated action.
In what concerns the influences of the three forms of the online intellectual capital on the consumption of bio products, the results highlighted two significant positive relationships between the online human capital and the consumption of bio products (ß = 0.166, p < 0.001) and the online relational capital and the consumption of bio products (ß = 0.459, p < 0.001), the latter retrieving the highest value among the path coefficients. The findings confirm the fact the evidence brought by Zhao et al. (2013) and Bharati et al. (2015), but fall short to account for the relationship between the online structural capital and the consumption of bio products (p > 0.05) in the context of the current research. Nevertheless, the indirect effect of digitalization on the consumption of bio products proved significant and positive (ß = 0.276, p < 0.001), thus supporting the impact of the digital economy from the demand-side standpoint. The results confirm the initial assumptions of the study in that the emergence of new forms of intellectual capital reconfigures the logic of the digital economy and supports the consolidation of knowledge-based consumption trends and of informed consumers. Moreover, the interest and consistent orientation of the online communities' members towards the consumption of bio products stand for a compelling catalyst for the bioeconomic model within today's macroeconomic context, by acknowledging the significant influence of the stakeholders.
Given the fact that the research sample included subjects from two different European countries (i.e., Romania and Italy), a multi-group analysis was performed in accordance with the recommendations of Sarstedt et al. (2011). This analysis allowed to examine whether there were statistically significant differences between the online consumers in the sample in relation to their country residence, as presented in table no. 4.
At this level, the analysis indicated that the differences between the two groups - i.e., Romanian subjects versus Italian subjects - are not meaningful (p > 0.05). In this way, evidence is brought that the validation of the inferred relationships is not only countryspecific, going beyond national delimitations.
Conclusions
Approaching bioeconomy from a demand-side perspective, the present paper discussed the effects of digitalization on the emergence and development of new forms of intellectual capital, objectivized within consumer-based online communities, and the effects of the latter on the consumption of bio products. In this vein, the active role of the online consumers was brought to the fore, with a special emphasis on the new generation of empowered consumers who cement knowledge-based consumption patterns.
In their search for bio products, online consumers share their expectations and preferences, their experience and expertise with similar peers, unfolding consistent knowledge exchanges. In this way, they acquire and transmit relevant knowledge on sustainable, biolabeled products, steadily supporting the transition to a new economic model, to a novel approach on market dynamics and consumption patterns. Here, even though the paper brings forward the importance of the large-scale consumption of bio products - understood as an incentive for the bioeconomic model from the demand side - a first research limit refers to the lack of examination of the economic sectors which produce, handle and exploit bio resources. Further research focused on the analysis of the offer of bio products would round off the frame of reference and would enrich the multifield landscape of bioeconomy.
The research included a sample comprising subjects from two European countries (i.e., Romania and Italy), the findings showing no statistically significant differences between the structural models applicable to country-specific contexts. In this vein, a second research limit is objectivized, given the convenience sampling and the structure of the sample itself which consists of subjects with an average age of 22 years. Future research would benefit from extending the study on samples from other European states and on other age categories in order to test potential cleavages.
Acknowledgement: This work was supported by a grant of Ministry of Research and Innovation, CNCS - UEFISCDI, project number PN-III-P1-1.1-TE-2016-0232, within PNCDIIII.
Please cite this article as:
Vătămănescu, E.-M., Alexandru, V.-A., Cristea, G., Radu, L. and Chirica, O., 2018. A Demand-Side Perspective of Bioeconomy: The Influence of Online Intellectual Capital on Consumption. Amfiteatru Economic, 20(49), pp. 536-552.
* Corresponding author, Elena-Mădălina Vătămănescu - [email protected]
References
Andrei, A.G., Zaiţ, A., Vătămănescu, E.-M. and Pînzaru, F., 2017a. Word of Mouth Generation and Brand Communication Strategy: Findings from an Experimental Study Explored with PLS-SEM. Industrial Management & Data Systems, 117(3), pp. 478-495.
Andrei, A.G., Gazzola, P., Zbuchea, A. and Alexandru, V.-A., 2017b. Modeling Socially Responsible Consumption and the Need for Uniqueness: A PLS-SEM Approach. Kybernetes, 46(8), pp. 1325-1340.
Barclay, D., Higgins, C. and Thompson, R., 1995. The Partial Least Squares (PLS) Approach to Causal Modeling: Personal Computer Adoption and Use as an Illustration. Technology Studies, 2(2), pp. 285-309.
Bina, O., 2013. The Green Economy and Sustainable Development: An Uneasy Balance?. Environment and Planning C: Government and Policy, 31(6), pp. 1023-1047.
Brătianu, C., 2009. The Frontier of Linearity in the Intellectual Capital Metaphor. In: C. Stam and D. Andriessen (eds.), 2009. Proceedings of the European Conference on Intellectual Capital, Inholland University of Applied Sciences. Reading: Academic Conferences and Publishing International. pp. 97-103.
Bharati, P., Zhang, W. and Chaudhury, A., 2015. Better Knowledge with Social Media? Exploring the Roles of Social Capital and Organizational Knowledge Management. Journal of Knowledge Management, 19(3), pp. 456-475.
Brodie, R. J., Ilic, A., Juric, B. and Hollebeek, L., 2013. Consumer Engagement in a Virtual Brand Community: An Exploratory Analysis. Journal of Business Research, 66(1), pp. 105-114.
Cheung, C.M., Lee, M.K. and Rabjohn, N., 2008. The Impact of Electronic Word-OfMouth: The Adoption of Online Opinions in Online Customer Communities. Internet Research, 18(3), pp. 229-247.
Cricelli, L., Greco, M. and Grimaldi, M., 2014. An Overall Index of Intellectual Capital. Management Research Review, 37(10), pp. 880-901.
Dabija, D.C., Babut, R., Dinu, V. and Lugojan, M.I., 2017. Cross-Generational Analysis of Information Searching Based on Social Media in Romania. Transformations in Business & Economics, 16(2), pp. 248-270.
Dabija, D.C., Bejan, B. and Tipi, N., 2018. Generation X versus Millennials Communication Behavior on Social Media when Purchasing Food versus Tourist Services. Economics and Management, 21(1), pp. 191-205.
Dean, A. and Kretschmer, M., 2007. Can Ideas Be Capital? Factors of Production in the Postindustrial Economy: A Review and Critique. Academy of Management Review, 32(2), pp. 573-594.
Diamantopoulos, A. and Siguaw, J.A., 2006. Formative versus Reflective Indicators in Organizational Measure Development: A Comparison and Empirical Illustration. British Journal of Management, 17(4), pp. 263-282.
Dominici, G., Yolles, M. and Caputo, F., 2017. Decoding the Dynamics of Value Cocreation in Consumer Tribes: An Agency Theory Approach. Cybernetics & Systems, 48(2), pp. 84-101.
Espejo, R. and Dominici, G., 2017. Cybernetics of Value Cocreation for Product Development. Systems Research & Behavioral Science, 34(1), pp. 24-40.
Euromonitor International, 2017. Global Changemakers: Real Market Impact of Empowered Consumers. [pdf] Available at: <http://go.euromonitor.com/white-paperindustry-2016-Global-Changemakers-Market-Impact-Empowered-Consumers.html> [Accessed 28 February 2018].
European Commission, 2011. Commission Staff Working Paper. Consumer Empowerment in the EU. [pdf] Available at: <http://ec.europa.eu/consumers/consumer_empowerment/ docs/swd_consumer_empowerment_eu_en.pdf> [Accessed 28 February 2018].
European Commission. 2017a. Sustainable and Optimal Use of Biomass for Energy in the EU Beyond 2020. [pdf] Available at: <https://ec.europa.eu/energy/sites/ener/files/ documents/biosustain_report_final.pdf> [Accessed 18 February 2018].
European Commission, 2017b. Cities for Food Systems Innovation and Green Jobs Steps towards food systems approaches for 2030 Research. Food 2030 Workshop Outcomes Report. [pdf] Available at: <file:///C:/Users/madal/Desktop/Articol%20AE%202018/ REPORT%20-%20food2030_workshop%20outcomes%20report_final_web.pdf> [Accessed 16 February 2018].
European Commission, 2012. Innovating for Sustainable Growth, A Bioeconomy for Europe. [pdf] Available at: <http://ec.europa.eu/research/bioeconomy/pdf/201202_ innovating_sustainable_growth_en.pdf> [Accessed 10 February 2018].
European Commission, 2010. Digital Agenda for Europe. [pdf] Available at: <http://eige.europa.eu/resources/digital_agenda_en.pdf> [Accessed 15 February 2018].
European Commission, 2005. New Perspectives on the Knowledge-Based Bio-Economy: Conference Report. [pdf] Available at: <http://edz.bib.uni-mannheim.de/daten/edzbra/gdre/05/kbbe_conferencereport.pdf> [Accessed 10 February 2018].
European Commission - Research Directorate-General, 2009. The European Knowledge Based Bio-Economy. [pdf] Available at: <https://ec.europa.eu/research/biotechnology/ eu-us-task-force/pdf/hallen_19_july_10-45_en.pdf > [Accessed 15 February 2018].
European Parliament, 2011. Consumer Behavior in a Digital Environment. [pdf] Available at: <http://www.europarl.europa.eu/RegData/etudes/etudes/join/2011/464441/IPOLIMCO_ET(2011)464441_EN.pdf> [Accessed 15 February 2018].
Eurostat, 2018. E-commerce Statistics for 2017. [online] Available at: <http://ec.europa.eu/ eurostat/statistics-explained/index.php/E-commerce_statistics_for_individuals# Further_Eurostat_information> [Accessed 4 March 2018].
Forman, C., Ghose, A. and Wiesenfeld, B., 2008. Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets. Information Systems Research, 19(3), pp. 291-313.
Fornell, C. and Larcker, D.F., 1981. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), pp. 39-50.
Gazzola, P., Colombo, G., Pezzetti, R. and Nicolescu, L., 2017. Consumer Empowerment in the Digital Economy: Availing Sustainable Purchasing Decisions. Sustainability, 9(5), pp. 693-712.
Hair, J.F., Hult, G.T.M., Ringle, C.M. and Sarstedt, M., 2014. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Los Angeles, CA: Sage.
Halttunen, V., 2016. Consumer Behavior in Digital Era: General Aspects and Findings of Empirical Studies on Digital Music with a Retrospective Discussion. Dissertation Paper. Jyväskylä: University of Jyväskylä.
Henseler, J., Ringle, C.M. and Sarstedt, M., 2015. A New Criterion for Assessing Discriminant Validity in Variance-Based Structural Equation Modeling. Journal of the Academy of Marketing Science, 43(1), pp. 115-135.
Henseler, J., Ringle, C. and Sinkovics, R., 2009. The Use of Partial Least Squares Path Modeling in International Marketing. Advances in International Marketing, 20(1), pp. 277-320.
Herremans, I.M., Isaac, R.G., Kline, T.J. and Nazari, J.A., 2011. Intellectual Capital and Uncertainty of Knowledge: Control by Design of the Management System. Journal of business ethics, 98(4), pp. 627-640.
Hobart, J.W. and Sendek, H., 2016. Generaţia Y: Generaţia Mileniului 3 si Evoluţia Leadershipului. Bucharest: BMI.
Lakatos, E.S., Cioca, L.I., Dan, V., Ciomos, A.O., Crişan, O.A. and Bârsan, G., 2018. Studies and Investigation about the Attitude towards Sustainable Production, Consumption and Waste Generation in Line with Circular Economy in Romania. Sustainability, 10(3), 865.
Le Blanc, D., 2011, August. Special Issue on Green Economy and Sustainable Development. Natural Resources Forum, 35(3), pp. 151-154.
Leitner, K.H., Curaj, A., Elena-Perez, S., Fazlagic, J., Kalemis, K., Martinaitis, Z. and Zaksa, K., 2014. A Strategic Approach for Intellectual Capital Management in European Universities: Guidelines for Implementation. Bucharest: UEFISCDI.
Maher, M., Reynolds, P., Muysert, P. and Wandschneider, F., 2016. Resetting Competition Policy Frameworks for the Digital Ecosystem. [pdf] Available at: <http://www.gsma.com/publicpolicy/wp-content/uploads/2016/10/ GSMA_Resetting-Competition_Report_Oct-2016_60pp_WEBv2.pdf> [Accessed 10 February 2018].
Mahler, D., 2016. Don't Give up on Millennials. [online] Available at: https://www.atkearney.com/america250/ don-t-give-up-on-millennials> [Accessed 23 February 2018].
Mazzucato, M. and Perez, C., 2014. Innovation as a Growth Policy. The Challenge for Europe. Working Paper Series SWPS 2014D13. University of Sussex. [online] Available at: <https://www.sussex.ac.uk/webteam/gateway/file.php?name=2014-13swps-mazzucato-perez.pdf&site=25> [Accessed 14 February 2018].
L j krík, A., 2015. Changes in Purchasing Decision-Making Process of Consumers in the Digital Era. European Journal of Science and Theology, 11(6), pp. 167-176.
Organisation for Economic Co-operation and Development (OECD), 2016. Consumer Protection in E-commerce: OECD Recommendation. [pdf] Available at: <https://www.oecd.org/sti/consumer/ECommerce-Recommendation-2016.pdf > [Accessed 14 February 2018].
Organisation for Economic Co-operation and Development (OECD), 2009. Consumer Education Policy Recommendations of the OECD'S Committee on Consumer Policy. [pdf] Available at: <http://www.oecd.org/internet/consumer/44110333.pdf> [Accessed 15 February 2018].
Organisation for Economic Co-operation and Development (OECD), 2008. Promoting Sustainable Consumption Good Practices In OECD Countries. [pdf] Available at: <https://www.oecd.org/greengrowth/40317373.pdf > [Accessed 17 February 2018].
Pyka, A., 2017. Dedicated Innovation Systems to Support the Transformation Towards Sustainability: Creating Income Opportunities and Employment in the KnowledgeBased Digital Bioeconomy. Journal of Open Innovation: Technology, Market, and Complexity, 3(1), p. 27-28.
Ringle, C.M., Wende, S. and Becker, J.-M., 2015. SmartPLS 3. Boenningstedt: SmartPLS GmbH.
Sarstedt, M., Henseler, J. and Ringle, C.M., 2011. Multi-group Analysis in Partial Least Squares (PLS) Path Modeling: Alternative Methods and Empirical Results. Advances in International Marketing, 22(1), pp. 195-218.
Sharabati, A.A.A., Jawad, S.N. and Bontis, N., 2010. Intellectual Capital and Business Performance in the Pharmaceutical Sector of Jordan. Management Decision, 48(1-2), pp. 105-131.
Soto-Acosta, P., Colomo-Palacios, R. and Popa, S., 2014. Web Knowledge Sharing and its Effect on Innovation: An Empirical Investigation in SMEs. Knowledge Management Research & Practice, 12(1), pp. 103-113.
Sogari, G., Pucci, T., Aquilani, B. and Zanni, L., 2017. Millennial Generation and Environmental Sustainability: The Role of Social Media in the Consumer Purchasing Behavior for Wine. Sustainability, 9(10), 1911.
Still, K., Huhtamäki, J. and Russell, M., 2014. New Insights for Relational Capital. IICICKM2014-Proceedings of the 11th International Conference on Intellectual Capital, Knowledge Management and Organisational Learning: ICICKM2014. Reading: Academic Conferences Limited.
Still, K., Huhtamäki, J. and Russell, M., 2013. Relational Capital and Social Capital: One or two Fields of Research? In: A. Green, ed. 2013. Proceedings of the 10th International Conference on Intellectual Capital, Knowledge Management and Organisational Learning. Reading: Academic Conferences Limited. pp. 420-428.
Subramaniam, M. and Youndt, M., 2005. The Innovation of Intellectual Capital on the Types of Innovative Capabilities. Academy of Management Review, 48(3), pp. 450-463.
Thompson, S.H.T., 2003. Assessing the Consumer Decision Process in the Digital Marketplace. Omega, 31(5), pp. 349-363.
Trigo, E.J., Henry, G., Sanders, J., Schurr, U. Ingelbrecht, C., Revel, C., Santana, C. and Rocha, P. 2013. Towards Bioeconomy Development in Latin America and the Caraibbean. Bioeconomy Working Paper, no.2013-01. Cali, Colombia: CIRAD ALCUE KBBE.
Tovstiga, G. and Tulugurova, E., 2007. Intellectual Capital Practices and Performance in Russian Enterprises. Journal of Intellectual Capital, 8(4), pp. 695-707.
UN Environment, 2018. What is an "Inclusive Green Economy"?. [online] Available at: <http://web.unep.org/greeneconomy/what-inclusive-green-economy> [Accessed 22 February 2018].
United Nations Conference on Trade and Development, 2011. The Green Economy: Trade and Sustainable Development Implications, 8-10 November 2011 Geneva, Switzerland. [pdf] Available at: <http://unctad.org/en/docs/ditcted2011d5_en.pdf > [Accessed 18 February 2018].
Unruh, C.G., 2000. Understanding Carbon Lock-in. Energy Policy, 28, pp. 817-830.
Van Gorp, N. and Batura, O., 2015. Challenges for Competition Policy in a Digitalised Economy. [pdf] Available at: <http://www.europarl.europa.eu/RegData/etudes/ STUD/2015/542235/IPOL_STU(2015)542235_EN.pdf> [Accessed 14 February 2018].
Vătămănescu, E.-M., Andrei, A. G., Dumitriu, D. L. and Leovaridis, C., 2016. Harnessing Network-Based Intellectual Capital in Online Academic Networks. From the Organizational Policies and Practices Towards Competitiveness. Journal of Knowledge Management, 20(3), pp. 594-619.
Vătămănescu, E.-M., Andrei, A.-G., Leovaridis, C. and Dumitriu, L.-D., 2015. Exploring Network-Based Intellectual Capital as a Competitive Advantage. An Insight into European Universities from Developing Economies. In: J.G. Cegarra Navarro, ed. 2015. Proceedings of the 7th European Conference on Intellectual Capital ECIC 2015. Reading: Academic Conferences and Publishing International Limited. pp. 350-358.
Vătămănescu, E.-M., Andrei, A.G. and Pînzaru. F., 2018. Investigating the Online Social Network Development through the Five Cs Model of Similarity: the Facebook Case. Information Technology & People, 31(1), pp. 84-110.
Wirtz, J., Den Ambtman, A., Bloemer, J., Horváth, C., Ramaseshan, B., Van De Klundert, J. and Kandampully, J., 2013. Managing Brands and Customer Engagement in Online Brand Communities. Journal of Service Management, 24(3), pp. 223-244.
World Bank (WB), 2016. Digital Dividends Report. [pdf] Available at: <http://wwwwds.worldbank. org/external/default/WDS ContentServer/WDSP/IB/2016/01/13/09022 4 b08405ea05/2_0/Rendered/PDF/World0developm0000digital0dividends.pdf> [Accessed 7 February 2018].
Yi, M.Y. and Davis, F.D., 2003. Developing and Validating an Observational Learning Model of Computer Software Training and Skill Acquisition. Information Systems Research, 14(2), pp. 146-169.
Zhao, Y., Yang, S., Narayan, V. and Zhao, Y., 2013. Modeling Consumer Learning from Online Product Reviews. Marketing Science, 32(1), pp. 153-169.
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Abstract
The present paper aims to address a demand-side perspective of bioeconomy by laying emphasis on the digitalization of markets and, subsequently, on the consumption patterns at the macroeconomic scale. The imperative for a sustainable economic model corroborated with the advances in digital technologies usage have reconfigured consumers' approaches and expectations and availed new forms of consumer behavior. Among these, the development of consumer-based online communities and of the online intellectual capital have often come forth as an undertaking of empowered consumers pursuing knowledgebased consumption patterns. The quest for sustainable, bio-labeled products on the digital markets has cemented the formation of new social aggregations built on the similarity of interests, goals, values, expectations, preferences, etc., giving way to consistent communication and interaction flows among their members and engendering profound transformations in today's society. Acknowledging all these facts, the study investigates the influences of the online intellectual capital on the consumption patterns through the lens of bioeconomy. The focus is set on the bio products consumption in two European countries (i.e., Romania and Italy), relying on a sample of over 700 active online consumers. Processed via a structural equation modeling technique, the data indicated the existence of significant influences among the considered variables.