Claudio Vitari

Elisabetta Raguseo

Technologies pour les données massives : bénéfices et coûts perçus par les entreprises adoptantes et non adoptantes

Keywords: technologies pour les données massives, coûts, bénéfices, adoption, digitalisation, perceptions big data, information technology, costs, benefits, digitalization, perceptions, adoption

Cette étude vise à identifier les différences de perception, parmi les entreprises, entre les adoptants et les non-adoptants des technologies pour les données massives (BDT) en termes de coûts et de bénéfices. Sur la base de la littérature et de recherches antérieures, un questionnaire a été conçu, y compris une étude pilote sur un sous-échantillon de la population ciblée d'entreprises. Au total, 200 questionnaires ont été remplis. L'échantillon final était composé de 86,5 % d'entreprises de taille moyenne et de 13,5 % de grandes entreprises, ce qui a permis d'assurer un niveau de confiance de 95 % et un intervalle de confiance de 6,9 %. Nous constatons des différences significatives entre les adoptants et les non adoptants des BDT en ce qui concerne la perception de leurs coûts et bénéfices. Par exemple, l'analyse a mis en évidence que les adoptants et les non-adoptants ont des perceptions différentes des bénéfices des BDT en termes de rentabilité : le taux de réussite des nouveaux produits ou services étant plus élevé que celui des concurrents et la croissance des ventes. Les non adoptants perçoivent que ces bénéfices sont inférieurs à la perception qu'ont les adoptants de ces bénéfices. Cette étude, en accord avec la théorie de la diffusion de l'innovation, identifie les différences de perception des coûts et des bénéfices entre les segments des entreprises qui adoptent les BDT et celles qui ne l'adoptent pas. En ce qui concerne les implications pratiques, nos résultats enrichissent les orientations dont disposent les dirigeants dans leurs décisions de mettre en oeuvre les BDT dans leurs entreprises.

1.Introduction

In the last decade, technological change due to digitalization has had a strong impact on the competitive dynamics of sectors, human-machine interaction and value creation opportunities for companies [START_REF] Kharlamov | The impact of servitization and digitization on productivity and profitability of the firm: a systematic approach[END_REF]. Technological change brings benefits in many areas, such as decision-making processes and labor markets [START_REF] Günther | Debating big data: A literature review on realizing value from big data[END_REF]. Particularly, in business, digital transformation is very important since it enables companies to react and manage changing markets [START_REF] Chen | Value creation by SMEs participating in global value chains under Industry 4.0 trend: Case Study of Textile Industry in Taiwan[END_REF]; it allows the automation of existing processes, i.e., the elimination of routine work [START_REF] Schmitz | Enabling digital transformation through robotic process automation at Deutsche Telekom[END_REF] and the transformation of their value proposition and the features of the products and services provided [START_REF] Frank | Servitization and Industry 4.0 convergence in the digital transformation of product firms: A business model innovation perspective[END_REF].

Innovative businesses are using a wide range of novel digital tools, ranging from apps to artificial intelligence, with significant benefits for their business models [START_REF] Loebbecke | Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda[END_REF], their strategies and the ways in which they manage customers. This wave of technology disruption has already transformed many industries for both customers and firms from both the demand and supply sides [START_REF] Constantiou | New games, new rules: big data and the changing context of strategy[END_REF]. From the customer side, for example, digital transformation plays a key part in delivering a better experience [START_REF] Wiener | Big-data business models: A critical literature review and multiperspective research framework[END_REF]. From the company side, artificial intelligence is revolutionizing companies' strategies and the way they set prices. Among all the technologies that are revolutionizing the sectors, big data technologies (BDT) allow one to extract, process and analyze huge amounts of data in order to extract value from them. Managers, especially those of medium-and large-sized firms, know their features and what the market is able to offer. There are studies in the literature that have shown the possible benefits and their features of BDT [START_REF] Ren | Modelling Quality Dynamics, Business Value and Firm Performance in a Big Data Analytics Environment[END_REF]. However, even though the literature has already investigated the costs and benefits involved in the adoption of BDT, the understanding is still scant, and the literature provides distinctive points of view of adopters and non-adopters regarding their perceptions of the benefits and costs of BDT. We focus on the benefits and costs because they contribute to determining the relative advantage of an innovation. The perceived relative advantage is the most significant innovation characteristic of the adoption process as part of the diffusion of innovation theory [START_REF] Rogers | Diffusion of innovations[END_REF]. Moreover, regarding this adoption behavior, we split the target population into adopters and non-adopters (e.g., [START_REF] Karayanni | Web-shoppers and non-shoppers: compatibility, relative advantage and demographics[END_REF][START_REF] Eastlick | Profiling potential adopters and non-adopters of an interactive electronic shopping medium[END_REF], which would provide the opportunity to reveal differences between the groups.

Given the increasing importance of BDT and their applications, the aim of this study is twofold. First, the study examines the perceived benefits of BDT by BDT adopters and nonadopters to understand if the benefits are different for the two groups of companies. Second, the study also investigates the perceived costs of this technology from the points of view of both adopters and non-adopters, highlighting the presence of possible differences and in which terms. Accordingly, in this study, we answer the following research question: "What are the differences in the perception of benefits and costs of BDT between BDT adopters and non-adopters?" The results will help to better understand the IT investments of companies around their information management.

The remainder of this article is structured as follows. First, we discuss the research already published on BDT in companies, and we then present our two hypotheses. Second, we highlight the research methodology. In the following, we present our findings, and we discuss them in light of the existing theory. Finally, we provide some implications for practice and the most pertinent avenues of future research, and we conclude the study.

Challenges of BDT in companies and hypotheses development

Even though the worldwide big data market is expected to account for USD 135.22 billion by 2025 with a growth rate of 19% from 2017 to 2025 [START_REF] Navanath | Big Data Market 2020 Growth Analysis, Opportunities, Trends, Developments and Forecast to 2026[END_REF], many CIOs and managers hesitate to make BDT investments since they are scared of the costs they could encounter and of the uncertainty regarding the real benefits for their companies. Many challenges to big data use are advanced by the literature [START_REF] Sivarajah | Critical analysis of Big Data challenges and analytical methods[END_REF], and they are of different natures and occur at different points in time throughout a BDT investment.

One of the first issues to solve is related to data life cycle management [START_REF] Li | Big data in product lifecycle management[END_REF] and the need to know how to collect, integrate and store the data from many sources [START_REF] Chen | Big data: related technologies, challenges and future prospects[END_REF]. Data can be generated at a high speed and in huge volumes; hence, these data need to be classified to understand which data need to be stored and which data need to be discarded since they are not valuable. Once this selection is over, data compression [START_REF] Zou | Improving I/O performance with adaptive data compression for big data applications[END_REF] could be considered. Gathered data could be reduced, compressed and filtered in order to be useful for managers. Moreover, the accuracy, timeliness, precision, reliability, currency, completeness, and relevancy of all data need to be assured when managers have to handle big data. For example, if the data gathered about customers are not timely, they may be much less useful or even completely obsolete. If data are not complete regarding, for example, customers' behavior in a shop, the data could hinder managers' decision making. Furthermore, the decision making is largely influenced by the data representation [START_REF] Brooker | Have we even solved the first 'big data challenge?'Practical issues concerning data collection and visual representation for social media analytics[END_REF]: when managers need to handle different types of data, they face heterogeneous types and structures of data at the same time. If companies have the right big data tools to represent data they possess, they can find the meaning of them more easily and interpret them properly.

From a longer perspective, the scalability of BDT investments has to be satisfied. The systems that support the storage and analysis of big data need to interconnect with existing databases as well as future databases. The analytical algorithms beyond them need to process databases that, over time, become more complex and increasingly large. However, this scalability toward future, new, and larger databases has to address the energy consumption issue [START_REF] Diamantoulakis | Big data analytics for dynamic energy management in smart grids[END_REF]. With the increase in the variety of data, the veracity and volume, and the analytical demands, processing, storage, and transmission of big data, companies will unavoidably consume increasingly more electric energy. Therefore, companies should have mechanisms that manage and control power consumption in order to ensure the accessibility and expandability of big data.

Perceived benefits of BDT

Given these challenges, evaluating how BDT benefits the creation of the business value of a company is extremely important (e.g., [START_REF] Mcafee | Big Data." The Management Revolution[END_REF][START_REF] Kiron | The Analytics Mandate[END_REF]Akter et al. 2016). Considering the previous literature, the main benefits of big data are focused on increasing financial performance, market performance and customer satisfaction [START_REF] Ren | Modelling Quality Dynamics, Business Value and Firm Performance in a Big Data Analytics Environment[END_REF]. Financial performance refers to the firm's ability to improve its profitability and return on investment. Market performance refers to a company's ability to enter new markets quicker than its competitors, introduce new products and services more frequently, have a higher success rate with its new products and services, and have a higher market share. Customer satisfaction is a function of how goods and services meet or surpass the expectations of customers. Indeed, customers compare the perceived performance of a product with a performance standard, and they are satisfied when the perceived performance is greater than the standard and dissatisfied when performance falls short of the standard [START_REF] Vorhies | Benchmarking Marketing Capabilities for Sustainable Competitive Advantage[END_REF].

However, since companies have difficulties in precisely computing the benefits of IT investments, the benefits are more perceived than calculated. These perceptions have nonetheless important consequences on the adoption of an innovation. The more that an innovation, such as BDT, is perceived as bringing benefits, the quicker the innovation will diffuse (Junglas et al. 2018). Hence, the companies that perceive that BDT delivers higher benefits adopt BDT while the companies that perceive that BDT delivers fewer benefits do not adopt BDT. Hence, our hypothesis is the following: H1. BDT adopters perceive BDT as more beneficial than BDT non-adopters.

Perceived costs of BDT

BDT does not deliver only benefits, including large or small benefits; and costs are another important factor in the adoption decision. Indeed, BDT results in new costs to sustain and to incur to successfully implement the BDT adopted and exploiting its potential. Most organizations have extensive experience in the management of traditional IT solutions, but these new technologies may represent new costs that can be handled differently. Therefore, managers, before making big data investments, need to know the costs they will incur. Moreover, companies need to consider both direct and indirect costs. Some examples of direct costs include hardware costs or upgrades to increase processing power. Conversely, indirect costs could be management and staff resources, ownership costs and management time (Love et al., 2015).

More specifically, studies dealing with the costs of BDT have described many issues including consultancy support costs (e.g., [START_REF] Turok | Developing expertise in small and medium-sized enterprises: an evaluation of consultancy support[END_REF]; installation engineers' costs (e.g., [START_REF] Singh | How Chief Digital Officers promote the digital transformation of their companies[END_REF]; overhead; training costs (e.g., [START_REF] Brown | The end of the credential society? An analysis of the relationship between education and the labour market using big data[END_REF]; and expenditures for maintenance, networking security, personnel and equipment for hardware and software.

However, given the notorious difficulties for companies in determining the actual IT costs, managers largely rely on their perceptions of costs when they need to take action. In line with the diffusion of innovation theory, costs play a central role in the adoption decision [START_REF] Wejnert | Integrating Models of Diffusion of Innovations: A Conceptual Framework[END_REF]. The higher the costs are, the longer the diffusion process will be. Hence, the companies that perceive that BDT has higher costs do not adopt BDT while the companies that perceive that BDT has lower costs adopt BDT. Hence, our hypothesis is the following: H2. BDT adopters perceive BDT as less costly than BDT non-adopters.

Research methodology

Data collection

A questionnaire was used to examine perceived benefits and costs of BDT adoption and to test our hypotheses. The questionnaire was distributed to medium-and large-sized French companies in 2016. In order to determine whether a company was medium or large sized, the European definition using the number of employees was considered. A medium-sized firm is a company with from 50 to 249 employees, while a large company has more than 249 employees.

As this study was conducted at the firm level, we followed the choice of previous studies (Jifan [START_REF] Ren | Modelling Quality Dynamics, Business Value and Firm Performance in a Big Data Analytics Environment[END_REF]) and targeted chief information officers (CIOs). A random sampling method was implemented to select 1,962 medium and large French companies from a population of 19,875 companies registered in the Bureau Van Dijk database to survey. The data gathering process involved three steps. In the first step, the companies were contacted in order to inform them of the aim of the research study and to ask permission to contact the CIO. In the second step, the CIOs were contacted and asked whether they were willing to participate in the survey. When the CIO was not available at the time agreed upon in the first call, a second appointment was made. Therefore, the questionnaire was filled in, either in the second or third step according to the availability of the CIO. When the CIO was not willing to reply to the questionnaire, another person qualified to answer questions regarding investments and the adoption of BDT was identified and completed the questionnaire.

First, a pilot study was conducted on a subsample of companies in order to test the comprehensibility of the questions included in the questionnaire, to identify any possible criticalities and to establish the expected response rate. All the responses were positive, and the questions appeared clear; therefore, the final questionnaire was unchanged. The response rate of the pilot test was 21.13% with 30 companies responding. After the pilot test, another 170 companies took part and completed the survey. Overall, 200 questionnaires were completed. The final sample was composed of 86.5% medium-sized companies and 13.5% large-sized companies, thus assuring a 95% confidence level and a 6.9% confidence interval, respectively (Table 1

Measures

The questionnaire adapted existing measures. To measure the adoption of BDT, a list of eight different BDT was compiled based on existing lists [START_REF] Gandomi | Beyond the hype: Big data concepts, methods, and analytics[END_REF][START_REF] Davenport | Big data at work: dispelling the myths, uncovering the opportunities[END_REF]. A multiple choice question was given to respondents to answer which BDT were adopted or if none was adopted. The eight BDT included the following:

1. MapReduce and Hadoop software or other software for processing big data across multiple parallel servers; 2. Scripting languages or other programming languages that work well with big data (e.g., Python, Pig, and Hive); 3. Machine learning software or other software for rapidly finding the model that best fits a data set; 4. Visual analytics software or other software for the display of analytical results in visual or graphic formats; 5. Natural language processing (NLP) software or other software for analyzing text and conducting information extraction, text summarization, question answering, and sentiment analysis; 6. In-memory analytics software or other processing big data in computer memory for greater speed; 7. Social media analytics software (content-based analytics and structure-based analytics); and 8. Predictive analytics software.

Additionally, the taxonomy used to investigate the perceived benefits and costs related to BDT that was adapted was based on previous research (Ji-fan [START_REF] Ren | Modelling Quality Dynamics, Business Value and Firm Performance in a Big Data Analytics Environment[END_REF][START_REF] Love | The enigma of evaluation: benefits, costs and risks of IT in Australian small-medium-sized enterprises[END_REF][START_REF] Wu | What Drives Mobile Commerce? An Empirical Evaluation of the Revised Technology Acceptance Model[END_REF][START_REF] Vorhies | Benchmarking Marketing Capabilities for Sustainable Competitive Advantage[END_REF]. Table 2 shows all the measurement items, which were based on a seven-point Likert scale, with responses ranging from "completely disagree" (-3) to "completely agree" (+3). Respondents were asked to evaluate the extent to which BDT led to benefits and costs.

Construct

Data analysis

A three-step procedure was followed to present the results. First, the percentages of adoption of the BDT were computed. Second, by focusing on the benefits side, the perceived benefits for adopters and non-adopters were computed to understand how benefits are perceived by adopters and non-adopters of BDT. An ANOVA test for every benefit was conducted between and within companies that adopt and do not adopt BDT. The ANOVA test between adopters and non-adopters allows us to understand which benefits are seen differently between the two subgroups of companies and which subgroup over-or underestimates their magnitude. The ANOVA test within companies that adopt and within companies that do not adopt gives us the ability to highlight the main benefits perceived by adopters and nonadopters. Third, by focusing on the costs side, the perceived costs for adopters and nonadopters were computed to understand how costs are perceived by adopters and non-adopters of BDT. An ANOVA test for every cost was conducted between companies that adopt and do not adopt BDT in order to understand which costs are seen differently between the two subgroups of companies and which subgroup over-or underestimates their magnitude. An ANOVA test for every cost was conducted within companies that adopt and within companies that do not adopt BDT in order to highlight which costs are considered the most burdensome within the two subgroups of companies.

Findings

Adoption of BDT

Figure 2 shows the adoption level of every BDT investigated in the questionnaire. Visual analytics software or other software for the display of analytical results in visual or graphic formats is the most adopted BDT among the medium and large companies investigated (40.8% of companies adopt this technology). These solutions allow one to explore, visualize and understand data better than separately examining the different sources. The second most adopted solution, by 38.2% of the companies, is related to scripting languages or other programming languages that work well with big data (e.g., Python, Pig, and Hive). The third most adopted technology is in-memory analytics software or other software for processing big data in computer memory for greater speed with an adoption rate equal to 30.3%. The less adopted BDT is predictive analytics software with just 15.80% of the companies choosing to use these software solutions.

Overall, these adoption trends demonstrate that companies invest more money in tools able to visualize and process data gathered in order to understand how to extract value from them instead of investing in solutions able to predict future trends. Another interesting result is based on the low adoption rate of software able to conduct content-based analytics of social media data, demonstrating the low propensity of companies to perform semantic analysis to understand customers' needs and behaviors.

Perceived benefits of BDT

Table 3 shows the results regarding the perceived benefits for adopters versus non-adopters of BDT and within each subsample. Overall, the mean scores of non-adopters and adopters of BDT reveal that the companies that perceive that BDT delivers more benefits are among the adopters of BDT, while the companies that perceive that BDT delivers fewer benefits are the non-adopters of BDT. Disaggregating benefits individually, the differences in the means between the two groups have an F statistic that is statistically significant at the 0.05 significance level for three benefits: profitability, the success rate of new products or services is higher than that of competitors, and sales growth. Moreover, the within-group differences indicate that, for adopters, profitability is perceived as the greatest benefit among the 11 types of benefits we listed. In addition to profitability, the success rate of new products or services being higher than that of competitors is equally important, as there is no statistically significant difference between the scores of these two kinds of benefits. Sales growth is ranked well behind the previous two benefits in the list of the main benefits. Regarding nonadopters, the order of the three benefits, which are perceived differently between the two groups, does not change: profitability is the most important benefit, sales growth is the third most important benefit, and the success rate of new products or services being higher than that of competitors is in the middle. Nonetheless, we noted that within non-adopters, the largest perceived benefit, among the whole list of 11 types of benefits, is improving the delivery of what customers want, which is hence higher than the perceived profitability of BDT.

Overall, we conclude that adopters and non-adopters of BDT have different perceptions regarding the impacts of BDT on their companies, highlighting that adopters perceived BDT as more beneficial than non-adopters in terms of profitability, sales growth and the success rate of new product and services. Therefore, Hypothesis 1 is partially supported.

Non-adopters Adopter

BDT benefits Mean

Perceived costs of BDT

Table 4 shows the results regarding the perceived costs for adopters versus non-adopters of BDT. Overall, the mean scores of non-adopters and adopters of BDT reveal that the companies that perceive that BDT increases costs are among the non-adopters of BDT while the companies that perceive that BDT decreases costs are adopters of BDT. Disaggregating costs individually, this difference in the means has an F statistic that is statistically significant at the 0.05 significance level for two of the costs: training costs and consultancy support.

Moreover, the within-group differences indicate that, for non-adopters, training costs are perceived as the largest cost among the nine types of costs we proposed; however, training costs do not seem to be a major issue for adopters, as it is the third lowest cost type among the nine types of costs. A similar gap in perception also appears for consultancy costs. While consultancy is among the costliest issues for non-adopters, consultancy is the second least expensive issue perceived by adopters. In contrast, we noted a sort of consensus on the costs of networking security and personnel. Networking security is perceived as the largest expense for adopters. Moreover, there is no significant difference in perception between adopters and non-adopters regarding networking security costs. Finally, networking security and joint training costs are the largest costs in the eyes of non-adopters. In contrast, both adopters and non-adopters perceive personnel costs to be the least expensive cost, and there is no significant difference in this perception between adopters and non-adopters.

In summary, adopters and non-adopters of BDT have different perceptions about the impacts of BDT on their companies, highlighting that adopters perceived BDT as being less costly than non-adopters in terms of training costs and consultancy support. Therefore, Hypothesis 2 is partially supported.

Discussion

We analyzed the differences in the perceptions between adopters and non-adopters. This analysis highlighted that adopters and non-adopters have different perceptions in terms of the benefits of BDT in terms of profitability, the success rate of new products or services being higher than that of competitors and sales growth. Non-adopters perceive that these benefits are lower than the perception that the adopters have regarding these benefits. Hence, we enrich the literature on the importance of evaluating how BDT benefits the creation of the business value of a company (e.g., [START_REF] Mcafee | Big Data." The Management Revolution[END_REF][START_REF] Kiron | The Analytics Mandate[END_REF]Akter et al. 2016). These differences could partially explain the decisions to adopt or to not adopt BDT. On the one hand, the firms that perceived fewer benefits from BDT will postpone the adoption of the BDT. On the other hand, the firms that perceived that BDT delivers large benefits are those that have already adopted these technologies. Stated differently, the companies that perceive that BDT delivers higher benefits adopt BDT while the companies that perceive that BDT delivers fewer benefits do not adopt BDT. These interpretations do not depart from the diffusion of innovation theory [START_REF] Rogers | Diffusion of innovations[END_REF] and confirm, for some benefits, our first hypothesis: BDT adopters perceive BDT as more beneficial than BDT nonadopters.

Additionally, when we analyze the perceived costs of BDT, we find indicators supporting the diffusion of innovation theory. Indeed, costs are another important factor in the adoption decision. As far as these new technologies may represent new costs, our approach provided evidence regarding the most important costs in BDT (Love et al., 2015). Training and networking security are the most important costs perceived by non-adopters while training is not perceived as a very expensive issue for BDT adopters. Hence, we enriched the list of costs of BDT available in the literature (e.g., [START_REF] Turok | Developing expertise in small and medium-sized enterprises: an evaluation of consultancy support[END_REF][START_REF] Singh | How Chief Digital Officers promote the digital transformation of their companies[END_REF][START_REF] Brown | The end of the credential society? An analysis of the relationship between education and the labour market using big data[END_REF], confirming some results, such as the importance of training costs (e.g., [START_REF] Brown | The end of the credential society? An analysis of the relationship between education and the labour market using big data[END_REF] and consultancy support costs (e.g., [START_REF] Turok | Developing expertise in small and medium-sized enterprises: an evaluation of consultancy support[END_REF], while minimizing others, such as personnel costs.

Moreover, our results highlight that there are differences in the perceived costs of BDT between adopters and non-adopters, particularly for training costs and consultancy support. Non-adopters perceive that the training costs and consultancy support are higher than the costs perceived by adopters. These differences could once more partially justify the decision to not adopt BDT for non-adopters and the decision to adopt BDT for BDT adopters. Since the non-adopters estimate that the costs of BDT are high, they do not invest in BDT. In contrast, the companies that perceived that the costs of BDT are low adopt BDT. These results echo the statements highlighting that many CIOs and managers hesitate to make BDT investments since they are scared of the costs that could exist and by the uncertainty about the real benefits in their companies [START_REF] Sivarajah | Critical analysis of Big Data challenges and analytical methods[END_REF].

Hence, the companies that perceive that BDT will burden the company with higher costs do not adopt the BDT, while the companies that perceive that BDT has lower costs do adopt the BDT, supporting, for some costs, our second hypothesis: BDT adopters perceive BDT as less costly than BDT non-adopters.

These teachings are important also for the BDT suppliers, as they can fine-grain their communication and commercial strategies toward their potential or actual customers, leveraging the customers' perceptions about the different costs and benefits of BDT.

Conclusion

The purpose of this paper was to develop a better understanding of the perceived benefits and costs, among enterprises, associated with the adoption of BDT between BDT adopters and non-adopters. A questionnaire was used to examine these aspects, and it was distributed to medium-and large-sized French companies. In so doing, the paper enriches the set of recommendations regarding how companies should proceed regarding their investments in BDT.

Key lessons learnt

Overall, the paper demonstrates that managers have different perceptions of the benefits and costs related to BDT. The relative importance of costs and benefits is different across adopters and non-adopters, and some costs and benefits are perceived as having different sizes between and within adopters and non-adopters. In general, adopters perceive that benefits are higher than non-adopters while non-adopters perceive higher costs than adopters. We consider that these differences in perceptions partially explain the decisions to adopt or not adopt BDT.

Implication for theory

The theoretical insights and the empirical findings discussed in this paper contribute to a more comprehensive view of benefits and costs of BDT and what managers should focus on when they adopt these technologies. Our results confirm that BDT can have a significant impact on competitive dynamics and value creation opportunities for companies [START_REF] Kharlamov | The impact of servitization and digitization on productivity and profitability of the firm: a systematic approach[END_REF]. Indeed, profitability and increased customer satisfaction are the preeminent benefits perceived by the adopters we sampled. Examining previous studies, our results agree on the importance of increasing financial performance and customer satisfaction while they underscore the previously measured contribution of BDT to market performance [START_REF] Ren | Modelling Quality Dynamics, Business Value and Firm Performance in a Big Data Analytics Environment[END_REF]. These perceptions are partially different from those of non-adopters who consider that improving the delivery of what customers want could be the greatest benefit of BDT and that profitability would be ranked only second.

The identification of these greatest advantages should not hide the other advantages recognized by respondents as far as respondents agreed, more than disagreed, on all the positive contribution of BDT across the 11 listed benefits with an exception regarding the increase of their market shares. Hence, this list of benefits can be added to the basket of benefits already highlighted in the literature [START_REF] Günther | Debating big data: A literature review on realizing value from big data[END_REF][START_REF] Chen | Value creation by SMEs participating in global value chains under Industry 4.0 trend: Case Study of Textile Industry in Taiwan[END_REF][START_REF] Schmitz | Enabling digital transformation through robotic process automation at Deutsche Telekom[END_REF][START_REF] Frank | Servitization and Industry 4.0 convergence in the digital transformation of product firms: A business model innovation perspective[END_REF][START_REF] Ren | Modelling Quality Dynamics, Business Value and Firm Performance in a Big Data Analytics Environment[END_REF][START_REF] Loebbecke | Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda[END_REF][START_REF] Wiener | Big-data business models: A critical literature review and multiperspective research framework[END_REF]. Moreover, our results come from a survey investigating a large number of different technologies, giving a robust understanding of the main benefits of a diversity of BDT rather than providing an exclusive focus on a specific kind of BDT.

Implications for practice

In terms of the implications for practice, our results enrich the available guidance that managers have at their disposal in their decisions to implement BDT in their companies. We provide a list of the benefits and costs that managers should consider. We provide them with the perceptions that adopters and non-adopters possess regarding BDT. For practitioners, we highlight the cost categories that are perceived as the most expensive by adopters and nonadopters and the differences between these two groups. Furthermore, we state the benefits that are perceived as the most important by adopters and non-adopters and their differences between groups. In this way, managers can seek to position their companies using the results of our sample and to exploit their perceptions to justify their decisions to adopt or not adopt BDT.

Limitations of this research

We recognize three main limitations of this research. Both are related to the adopted methodology: a survey across a representative sample of French companies, collecting perceptual data from enterprise managers. First, our results are mainly based on perceptions about costs and benefits of BDT. Even if these perceptions are expressed by managers they could provide a partial and subjective view on BDT and their impact on the managers' companies. We should take this limit into account when interpreting the results. Second, we collected survey data from 200 enterprises that represent the medium and large French companies. The extension of this data collection limits the deepness of the investigation. Hence, we do not have insights highlighting how these perceptions on costs and benefits are generated and we do not know why enterprises adopted or did not adopt BDT. Finally, we interviewed only French companies and we do not know to what extent our results are precise outside the investigated country as far as our sample is representative only of the French enterprise population.

Future research recommendations

Regarding the avenues of future research, as our results are based on perceptions, future studies could investigate the same topic by examining different kinds of measures for costs and benefits in order to prove the robustness of our results with different instruments, such as financial data coming directly from companies or indirectly through financial databases. This move would also give space to translate the relative scores of our survey into more intersubjective or objective scores. Conversely, case studies would deepen our cross-sectional data by highlighting the mechanisms behind the adoption choices of managers. In this way, it would be possible to precisely consider all the costs and benefits that BDT investments have for companies. Future studies should also focus on other countries in order to verify the generalizability of the findings and provide the same managerial advice to managers that belong to different locations.

Figure 1

 1 Figure1summarizes the relationships investigated in this study and the hypotheses tested.

Figure

  Figure 1 : Relationships investigated

Figure 2 .

 2 Figure 2. Adoption of BDT (base: all companies)

Table 1 . Sample characteristics

 1 ).

	No. = 200	Percentage
		(%)

Table 2 . Benefits and costs of BDT

 2

Table 3 . Benefits of BDT: adopters versus non-adopters (with F statistic, significant at 0.05 level, in bold)

 3

Table 4 . BDT costs: adopters versus non-adopters (with the F statistics significant at the 0.05 level in bold)

 4


Wander Pérez-Sena

Xiaoshuang Cai

Nasreddine Kebir

Lamiae Vernières-Hassimi

Christophe Serra

Tapio Salmi

Sébastien Leveneur
email: sebastien.leveneur@insa-rouen.fr

Y Pérez-Sena

Aminolysis of cyclic-carbonate vegetable oils as a non

Keywords: Polyurethane, Vegetable Oils, Kinetic Model, Calorimetry

Introduction

In the last years, the production of polyurethane has significantly increased. The global production of this polymer was close to 20 Mt in 2014 making it among the 6 polymers the most produced [START_REF] Orgiles-Calpena | Synthesis of polyurethanes from CO2-based polyols: A challenge for sustainable adhesives[END_REF]. This is due to the versatile properties of polyurethanes (PUs). Indeed, the application of these polyurethane materials can be found in different fields such as ship industry, health sector, automotive or bedding [START_REF]The ICI Polyurethanes book[END_REF][START_REF] Stanzione | Bio-based polyurethane foams from renewable resources[END_REF].

Production of PUs is commonly done by the reaction of polyols with di-isocyanates. Polyols can be produced from renewable feedstock like vegetable oils or their derivatives [START_REF] Pardieu | Polydopamine-coated open cell polyurethane foams as an inexpensive, flexible yet robust catalyst support: a proof of concept[END_REF][START_REF] Petrovic | Polyurethanes from vegetable oils[END_REF][START_REF] Lligadas | Renewable Polyols for Polyurethane Synthesis via Thiol-ene/yne Couplings of Plant Oils[END_REF]. On the contrary, diisocyanate reactant is a petroleum -derived product from the reaction of an amine on phosgene, which is unstable and toxic [START_REF] Kreye | Sustainable routes to polyurethane precursors[END_REF]. Academic community has extensively studied the nonisocyanate route for the production of PUs and the cyclic-carbonate/amine route is more and more interesting for industry [START_REF] Maisonneuve | Isocyanate-Free Routes to Polyurethanes and Poly(hydroxy Urethane)s[END_REF]. One of the most developed pathways is the reaction between a fivemembered bicyclocarbonate and a diamine [START_REF] Kreye | Sustainable routes to polyurethane precursors[END_REF][START_REF] Tomita | Polyaddition of bis(seven-membered cyclic carbonate) with diamines: A novel and efficient synthetic method for polyhydroxyurethanes[END_REF][START_REF] Del Rio | Biobased Polyurethanes from Polyether Polyols Obtained by Ionic-Coordinative Polymerization of Epoxidized Methyl Oleate[END_REF][START_REF] Ochiai | Branched cationic polyurethane prepared by polyaddition of chloromethylated five-membered cyclic carbonate and diethylenetriamine in molten salts[END_REF][START_REF] Deepa | Solvent-induced self-organization approach for polymeric architectures of micropores, hexagons and spheres based on polyurethanes prepared via novel melt transurethane methodology[END_REF][START_REF] Ochiai | Synthesis and properties of polyhydroxyurethane bearing silicone backbone[END_REF][START_REF] Kathalewar | Non-isocyanate polyurethanes: from chemistry to applications[END_REF][START_REF] Duval | Organocatalytic synthesis of novel renewable nonisocyanate polyhydroxyurethanes[END_REF][START_REF] Cornille | A perspective approach to sustainable routes for non-isocyanate polyurethanes[END_REF][START_REF] Figovsky | Non-isocyanate polyurethanesyesterday, today and tomorrow[END_REF].

Synthesis of five-membered cyclic-carbonates can be done by several routes: reaction between CO2 and 1,2-diols [START_REF] Zhao | Method for synthesizing propylene carbonate ester from CO2 and 1, 2-propanediol, CN 101376632A[END_REF] or between oxirane group and γ-butyrolactone [START_REF] Nishikubo | Convenient syntheses of cyclic carbonates by new reaction of oxiranes with β-butyrolactone[END_REF]. The most common way for the production of cyclic-carbonates is the gas-liquid reaction between CO2 and oxirane groups [START_REF] Fleischer | Glycerol-, pentaerythritol-and trimethylolpropanebased polyurethanes and their cellulose carbonate composites prepared via the non-isocyanate route with catalytic carbon dioxide fixation[END_REF][START_REF] Bähr | Linseed and soybean oil-based polyurethanes prepared via the nonisocyanate route and catalytic carbon dioxide conversion[END_REF][START_REF] Foltran | Solubility in CO2 and swelling studies by in situ IR spectroscopy of vegetable-based epoxidized oils as polyurethane precursors[END_REF].

Different research groups [START_REF] Maisonneuve | Isocyanate-Free Routes to Polyurethanes and Poly(hydroxy Urethane)s[END_REF][START_REF] Blain | Rational investigations in the ring opening of cyclic carbonates by amines[END_REF][START_REF] Tomita | Model reaction for the synthesis of polyhydroxyurethanes from cyclic carbonates with amines: Substituent effect on the reactivity and selectivity of ring-opening direction in the reaction of five-membered cyclic carbonates with amine[END_REF][START_REF] Garipov | Reactivity of cyclocarbonate groups in modified epoxy-amine compositions[END_REF][START_REF] Garipov | Study of the curing kinetics for modified epoxy amine systems using model compounds[END_REF][START_REF] Zabalov | Mechanism of urethane formation from cyclocarbonates and amines: a quantum chemical study[END_REF][START_REF] Burgel | Epoxy-Resins with Cyclic Carbonate Structures -Model Studies for Amine Curing[END_REF][START_REF] Tomita | Structural analysis of polyhydroxyurethane obtained by polyaddition of bifunctional five-membered cyclic carbonate and diamine based on the model reaction[END_REF][START_REF] Couvret | Acrylic-monomers containing a cyclic carbonate function .2. chemical modification of copolymers with pendent cyclic carbonate groups[END_REF][START_REF] Nemirovsky | Kinetic study of aminolysis of poly(vinylene carbonate) and related model compounds[END_REF][START_REF] Burgel | Reactions of Cyclic Carbonates with Amines -Model Studies for Curing Process[END_REF][START_REF] Ochiai | Kinetic and computational studies on aminolysis of bicyclic carbonates bearing alicyclic structure giving alicyclic hydroxyurethanes[END_REF][START_REF] He | Synthesis, Characterization, and Selectivity of Bifunctional Couplers[END_REF][START_REF] Maisonneuve | Fatty acid-based (bis) 6membered cyclic carbonates as efficient isocyanate free poly(hydroxyurethane) precursors[END_REF][START_REF] Levina | Nonisocyanate polyurethanes from amines and cyclic carbonates: Kinetics and mechanism of a model reaction[END_REF][START_REF] Lambeth | Organocatalytic synthesis of (poly)hydroxyurethanes from cyclic carbonates and amines[END_REF] have studied the kinetics of aminolysis for cyclic-carbonate compounds. In the review of the non-isocyanate routes for the production of polyurethanes, Maissoneuve et al. [START_REF] Maisonneuve | Isocyanate-Free Routes to Polyurethanes and Poly(hydroxy Urethane)s[END_REF] have summarized the kinetics of cyclic-carbonate aminolysis described in the following references [START_REF] Blain | Rational investigations in the ring opening of cyclic carbonates by amines[END_REF][START_REF] Tomita | Model reaction for the synthesis of polyhydroxyurethanes from cyclic carbonates with amines: Substituent effect on the reactivity and selectivity of ring-opening direction in the reaction of five-membered cyclic carbonates with amine[END_REF][START_REF] Garipov | Reactivity of cyclocarbonate groups in modified epoxy-amine compositions[END_REF][START_REF] Garipov | Study of the curing kinetics for modified epoxy amine systems using model compounds[END_REF][START_REF] Zabalov | Mechanism of urethane formation from cyclocarbonates and amines: a quantum chemical study[END_REF][START_REF] Burgel | Epoxy-Resins with Cyclic Carbonate Structures -Model Studies for Amine Curing[END_REF][START_REF] Tomita | Structural analysis of polyhydroxyurethane obtained by polyaddition of bifunctional five-membered cyclic carbonate and diamine based on the model reaction[END_REF][START_REF] Couvret | Acrylic-monomers containing a cyclic carbonate function .2. chemical modification of copolymers with pendent cyclic carbonate groups[END_REF][START_REF] Nemirovsky | Kinetic study of aminolysis of poly(vinylene carbonate) and related model compounds[END_REF][START_REF] Burgel | Reactions of Cyclic Carbonates with Amines -Model Studies for Curing Process[END_REF][START_REF] Ochiai | Kinetic and computational studies on aminolysis of bicyclic carbonates bearing alicyclic structure giving alicyclic hydroxyurethanes[END_REF][START_REF] He | Synthesis, Characterization, and Selectivity of Bifunctional Couplers[END_REF][START_REF] Maisonneuve | Fatty acid-based (bis) 6membered cyclic carbonates as efficient isocyanate free poly(hydroxyurethane) precursors[END_REF][START_REF] Levina | Nonisocyanate polyurethanes from amines and cyclic carbonates: Kinetics and mechanism of a model reaction[END_REF][START_REF] Lambeth | Organocatalytic synthesis of (poly)hydroxyurethanes from cyclic carbonates and amines[END_REF]. It appears that the reaction is of second order in aprotic solvent, and the kinetics depends on the nature of the solvent. It was also pointed out that at higher reaction temperature, i.e., above 100 °C, some side reactions can occur.

One can also cite the references of Levina et al. [START_REF] Levina | Nonisocyanate polyurethanes from amines and cyclic carbonates: Kinetics and mechanism of a model reaction[END_REF] and Lambeth and Henderson [START_REF] Lambeth | Organocatalytic synthesis of (poly)hydroxyurethanes from cyclic carbonates and amines[END_REF]. They have also noticed that the kinetics of reaction was of second order.

Except the work of Maisonneuve et al. [START_REF] Maisonneuve | Fatty acid-based (bis) 6membered cyclic carbonates as efficient isocyanate free poly(hydroxyurethane) precursors[END_REF], no studies were performed by using carbonated triglycerides or by using free fatty acids. Aminolysis of carbonated vegetable oils for the production of polyurethane requires the knowledge of kinetic and thermodynamic data for an industrial scale-up. To the best of our knowledge, no such data can be found in the literature. The goal of this study is thus to fill this gap by developing a kinetic model for this reaction system. Aminolysis of carbonated methyl oleate by n-butylamine was chosen as a model system. Fig. S1 shows the evolution of the viscosity with temperature for the different species, i.e., urethane, ester, epoxidized and carbonated. One can notice that the viscosity of oleic acid (OA) is higher than methyl oleate (MO). The viscosity increases using the epoxidized or carbonated forms. Thus, to avoid any mixing problem due to viscosity, oleic acid was esterified.

The first steps were to optimize the production of methyl oleate, epoxidized methyl oleate, and carbonated methyl oleate (Fig. 1). In the second part, a kinetic model was built by taking into account the amidation reaction, which is a side reaction. HERE Fig. 1. Synthesis of methyl oleate based urethane.

Experimental section

Materials

The following chemicals were used: oleic acid (purity ≥ 82 wt%), methanol (purity ≥ 99 wt%), formic acid (purity > 98 wt%) and hydrogen peroxide (purity ≥ 33 wt%) were purchased from VWR Chemicals. Sulfuric acid (purity ≥ 95 wt%) was obtained from AppliChem. Magnesium sulfate (purity ≥ 99.5 wt%) was obtained from Sigma Aldrich. Tetrabutylammonium bromide (TBABr) and n-butyl amine (purity ≥ 99.5 wt%) were supplied by Alfa Aesar.

Analytical methods

A gas chromatography (Bruker SCION 436-GC) equipped with a split injector and an elastic quartz capillary column (ZB-5, Phenomenex, 30 m × 0.32 mm i.d., 0.25 μm film thickness) was applied determine the conversion of oleic acid to methyl oleate in the esterification step (Fig. S2).

The yield of epoxide group during the epoxidation reaction was determined by the method of Jay [START_REF] Swern | Determination of Oxirane Oxygen[END_REF], where oil samples were dissolved in a solution of 10 mL of tetra-n-etylammonium bromide (20 wt% in acetic acid) and 10 mL of chloroform, then titrated with a TIM-840 automatic titrator (Radiometer Analytical, France) using a 0.1 N perchloric acid solution in acetic acid.

Otherwise, the conversion of unsaturated group was determined through titration of the iodine value using the method of Hanus [START_REF] Paquot | Standard methods for the analysis of oils, fats and derivatives[END_REF]. Unsaturated group reacts with iodine monobromide forming halogenated single bonds. Then, a potassium iodine solution was added causing the reaction of the remaining unreacted iodine in sample, which forms molecular iodine. Molecular iodine presented in sample can be titrated using a standard solution of sodium thiosulfate (0.1 N) and ferroin indicator [START_REF]Animal and vegetable fats and oils -Determination of iodine value[END_REF]. 1 H-NMR spectra were recorded on a Bruker 300 Fourier transform spectrometer at 300 MHz in CDCl3 solutions using tetramethylsilane (TMS) as internal standard.

IR spectra were recorded on a FTIR (Perkin-Elmer Spectrum 2000 FTIR), equipped with a diamond ATR device (Attenuated Total Reflection). Spectra were obtained from 10 scans in the (4000 to 500) cm -1 range. The enthalpies of reaction were measured using a Tian-Calvet heat flow calorimeter C80 (Setaram, France).

Viscosity measurement was performed with the aid of a Höppler viscometer (Fungilab S/A, Barcelona, Spain).

It was found that there is a linear relationship between the concentrations of ester and carbonated groups and their corresponding intensity signals from FTIR-analyses (eqs (1-2)).

[𝐶𝑎𝑟𝑏𝑜𝑛𝑎𝑡𝑒𝑑] = A 𝐶𝑎𝑟𝑏 • 𝐴𝑏𝑠 1802𝑐𝑚 -1 + B 𝐶𝑎𝑟𝑏 (1)
[𝐸𝑠𝑡𝑒𝑟] = A 𝐸𝑠𝑡𝑒𝑟 • 𝐴𝑏𝑠 1738𝑐𝑚 -1 + B 𝐸𝑠𝑡𝑒𝑟 (2)
where, [Carbonated] and [Ester] stand for the concentration of carbonated group and ester group.

Ai and Bi are characteristic constants of the FTIR equipment; Abs is the intensity of the signal at the corresponding wavelength. Figs. S3 and S4 show the linear correlation between the concentrations of ester and carbonated groups.

Production of intermediates

Oleic acid esterification

The reaction was carried out in a 500 mL reactor equipped with a mechanical stirrer and reflux condenser. Oleic acid (OA), methanol and sulfuric acid were mixed at a constant temperature of 64 °C with the following molar percentage: 19.2 %, 79.8 % and 1.0 %, respectively [START_REF] Nicolau | The polymerization products of epoxidized oleic acid and epoxidized methyl oleate with cis-1,2cyclohexanedicarboxylic anhydride and triethylamine as the initiator: Chemical structures, thermal and electrical properties[END_REF]. The reaction took 3 h. Next, the mixture was washed five times with preheated distillated water. Then, the organic phase left in the reactor was evaporated using an IKA RV10 control vacuum rotary evaporator (VWR, Darmstadt, Germany) at 70 °C and dried over anhydrous magnesium sulfate.

The final products were analyzed by FITR, GC (Fig. S2) and 1 H-NMR analysis.

Epoxidation of methyl oleate

The preparation of epoxidized methyl oleate (EMO) from methyl oleate (MO) was carried out in a 500 mL glass-jacketed reactor equipped with a mechanical stirrer and reflux condenser. The epoxidation was conducted in semi-batch mode, methyl oleate and formic acid were mixed at 40 °C, then hydrogen peroxide was added with a volumetric flow rate of 7.3 mL.min -1 for 1 h. The methyl oleate:formic acid:hydrogen peroxide molar ratio was 1:2:13. The reaction was performed for 4 h. The organic layer (containing the epoxide groups) was separated and washed with water to remove residual H2O2 and acids, followed by evaporation and dried over anhydrous magnesium sulfate [START_REF] Nicolau | The polymerization products of epoxidized oleic acid and epoxidized methyl oleate with cis-1,2cyclohexanedicarboxylic anhydride and triethylamine as the initiator: Chemical structures, thermal and electrical properties[END_REF]. Fig. 2 illustrates a simplified scheme of the reactor setup. HERE Fig. 2. Simplified reactor scheme for the epoxidation.

Carbonation of epoxidized methyl oleate

The carbonated methyl oleate (CMO) was prepared in a 300 mL autoclave equipped with a mechanical stirrer under pressure of carbon dioxide, TBABr was used as catalyst. Fig. 3 shows a simplified scheme of the reactor setup. Based on recent investigations [START_REF] Boyer | Solubility in CO2 and carbonation studies of epoxidized fatty acid diesters: towards novel precursors for polyurethane synthesis[END_REF][START_REF] Cai | Influence of gas-liquid mass transfer on kinetic modeling: Carbonation of epoxidized vegetable oils[END_REF][START_REF] Zheng | Carbonation of Vegetable Oils: Influence of Mass Transfer on Reaction Kinetics[END_REF][START_REF] Mazo | Carbonation of Epoxidized Soybean Oil Improved by the Addition of Water[END_REF][START_REF] Javni | Soy-based polyurethanes by nonisocyanate route[END_REF][START_REF] Büttner | Iron-Based Binary Catalytic System for the Valorization of CO2 into Biobased Cyclic Carbonates[END_REF], the optimum process conditions for carbonation reaction were 130 °C, 30 bar of CO2 pressure with a catalyst loading of 7 mol%. After eight hours of reaction, the conversion of epoxide group was 99 %. The resulting CMO was diluted in ethyl acetate, and washed four times with distilled water in order to remove TBABr catalyst, the product was dried with a rotary evaporator at 70 °C, and then anhydrous magnesium sulfate was used to dry traces of water before the aminolysis [START_REF] Doll | Synthesis of Carbonated Fatty Methyl Esters Using Supercritical Carbon Dioxide[END_REF].

HERE Fig. 3. Simplified reactor scheme for the carbonation.

Aminolysis reaction

Aminolysis was carried out under semi-batch mode in a 300 mL reactor equipped with a mechanical stirrer and a reflux condenser by reacting carbonated methyl oleate (CMO) and n-butyl amine (nBA) to produce urethanized methyl oleate (UMO). The latter reactant was added dropwise to avoid rapid temperature increase. The reactor setup is similar to the one shown in Fig. 2. The influences of temperature and feed flow rate were studied. The concentrations of urethane and ester groups were estimated by FTIR analysis. Indeed, there is a side reaction, which is the amidation of the ester groups [START_REF] Maisonneuve | Isocyanate-Free Routes to Polyurethanes and Poly(hydroxy Urethane)s[END_REF][START_REF] Javni | Polyurethanes from soybean oil, aromatic, and cycloaliphatic diamines by nonisocyanate route[END_REF][START_REF] Poussard | Non-isocyanate polyurethanes from carbonated soybean oil using monomeric or oligomeric diamines to achieve thermosets or thermoplastics[END_REF]. The products were also characterized by titration and 1 H-NMR analysis.

The experimental matrix used for the parameter estimation is displayed in Table 1. The term Qfeed stands for the volumetric flow rate of n-butylamine.

HERE Table 1. Experimental matrix.

Calorimetry

Reaction enthalpies were measured in a Tian-Calvet calorimeter (C80 Setaram) under isothermal mode. It is a twin calorimeter with a measured and reference cells in reversal mode. Fig. 4 shows a schematic view of the setup inside the calorimeter. Approximately 1 gram of sample was inserted in both the reference and measuring cells. Once the temperature and the flow heat rate in the cells were stable, the reaction was started. The heat flow released during the reaction course is due to the chemical reaction. More information about this system can be found in the references of our group [START_REF] Zheng | Kinetic modeling strategy for an exothermic multiphase reactor system: Application to vegetable oils epoxidation using Prileschajew method[END_REF][START_REF] Leveneur | Interaction of thermal and kinetic parameters for a liquid-liquid reaction system: Application to vegetable oils epoxidation by peroxycarboxylic acid[END_REF][START_REF] Jogunola | Complexation equilibria studies of alkyl formate hydrolysis in the presence of 1-butylimidazole[END_REF].

To determine the reaction enthalpies of aminolysis and amidation, two experiments were performed.

In the first experiment, the measurement cell was filled with CMO in one compartment and with n-butylamine in the other one, and the reference cell was filled with CMO in one compartment and with ethyl acetate in the other one (Fig. 4a). Ethyl acetate was chosen because it does not react with CMO and has similar specific heat capacity, as is the case with n-butylamine. Since there are no reactions in the reference cell, the total energy released by the system was the one for aminolysis and amidation reactions.

In the second experiment, the measurement cell was filled with CMO in one compartment and with n-butylamine in the other one, and the reference cell was filled with methyl oleate (MO) in one compartment and with n-butylamine in the other one (Fig. 4b). In the reference cell, amidation reaction also occurred, thus, the total energy released by the system was the one for aminolysis reaction.

HERE Fig. 4. Reversal mixing cells of C80 calorimeter.

Results and discussion

Product characterization

Oleic acid esterification

Since the esterification is a reversible reaction [START_REF] Stoker | General, organic, and biological chemistry[END_REF], a large molar excess of methanol was used to favor the ester formation. The maximum yield obtained was 93 % confirmed by GC analysis. Fig. 5 shows the FTIR spectra of oleic acid (OA) and methyl oleate (MO). The absorption band of ester group is at 1738 cm -1 , which confirms the production of methyl oleate during the reaction.

Otherwise, the band at 1710 cm -1 corresponds to carbonyl of residual acid groups. 1 H-NMR spectra (Fig. 6) also confirm the quantitative conversion of oleic acid to methyl oleate from the emergence of the corresponding signal of methyl ester group at 3.66 ppm as well as from the displacement of the signal of methylene group in alpha position to acid group from 2.34 ppm to 2.29 ppm.

HERE Fig. 5. FTIR-spectra for OA, MO, EMO, CMO and UMO.

Epoxidation of methyl oleate

The concentration of epoxide groups was followed by titration using a 0.1 mol.L -1 perchloride acid solution. The maximum concentration was reached after 4 h, with an epoxy yield of 91 % and a conversion of 98 % for double bonds. To minimize the side reaction of ring-opening, the most appropriate time was 4 h. The FTIR spectra of epoxidized methyl oleate (Fig. 5) shows the appearance of bands between 815 -950 cm -1 , which are related to stretching vibration of epoxide groups. Compared to methyl oleate, the disappearance of the band in the range of 3000 -3050 cm - 1 showed that the unsaturated groups were consumed [START_REF] Deshpande | Chemical modifications of lipids for applications in chemical industry[END_REF]. Furthermore, 1 H-NMR revealed that the signal at 5.34 ppm arising from carbon-carbon double bonds has disappeared (Fig. 6). Epoxide formation was confirmed by the appearance of a signal at 2.90 ppm [START_REF] Nicolau | The polymerization products of epoxidized oleic acid and epoxidized methyl oleate with cis-1,2cyclohexanedicarboxylic anhydride and triethylamine as the initiator: Chemical structures, thermal and electrical properties[END_REF]. HERE Fig. 6. 1 H-NMR for OA, MO, EMO, CMO and UMO.

Carbonation of Epoxidized methyl oleate

As illustrated in Fig. 7, CMO was prepared by converting the epoxide group of EMO with carbon dioxide in the presence of TBABr as catalyst. The oxirane ring of methyl oleate was attacked by the bromide of the catalyst leading to ring opening, followed by the nucleophilic attack of the alkoxide. Then, the five-membered carbonate was produced by the ring closure reaction of the resulting carboxylate [START_REF] Doll | Synthesis of Carbonated Fatty Methyl Esters Using Supercritical Carbon Dioxide[END_REF][START_REF] Langanke | Substrate dependent synergetic and antagonistic interaction of ammonium halide and polyoxometalate catalysts in the synthesis of cyclic carbonates from oleochemical epoxides and CO2[END_REF][START_REF] North | Mechanism of Cyclic Carbonate Synthesis from Epoxides and CO2[END_REF][START_REF] Lang | Green Catalytic Process for Cyclic Carbonate Synthesis from Carbon Dioxide under Mild Conditions[END_REF].

HERE Fig. 7. Conversion of epoxidized methyl oleate to carbonated methyl oleate.

The optimum conditions (load of catalyst, pressure, temperature) for the carbonation reaction have been studied before, concluding that a catalyst loading higher than 7 mol% barely increases the conversion rate [START_REF] Nicolau | The polymerization products of epoxidized oleic acid and epoxidized methyl oleate with cis-1,2cyclohexanedicarboxylic anhydride and triethylamine as the initiator: Chemical structures, thermal and electrical properties[END_REF]. During the investigation made by Ait Aissa et al. [START_REF] Ait Aissa | Thermal Stability of Epoxidized and Carbonated Vegetable Oils[END_REF], a thermal stability analysis of the catalyst was carried out, and it was found that temperature higher than 130 °C can cause a decomposition of TBABr, and subsequently the diminution of selectivity due to the formation of undesired secondary products. In this sense, the conditions for the carbonation of epoxidized methyl oleate were carefully optimized, with a temperature of 130 °C and a fixed pressure of 30 bar. A reaction time of 8 hours was selected, resulting in a 99 % conversion of epoxide groups.

The FTIR spectrum of CMO (Fig. 5) shows a strong band at 1800 cm -1 corresponding to the carbonate group. This band has a similar height with the one of ester group at 1738 cm -1 , which denotes similar concentration according to the literature [START_REF] Javni | Soy-based polyurethanes by nonisocyanate route[END_REF], and that the yield of carbonated group is high. The absence of absorption bands of epoxide group between 815-950 cm -1 confirms the fact that the conversion of epoxide group to carbonated groups is high. 1 H-NMR spectra showed signals between 4.40-4.95 ppm assigned to carbonated groups [START_REF] Swern | Determination of Oxirane Oxygen[END_REF].

Aminolysis reaction of carbonated methyl oleate

Fig. 1 shows the reaction of carbonated methyl oleate with n-butylamine. In this reaction system, two reactions occur: aminolysis, and amidation as a side reaction. The products were analyzed by FTIR and 1 H-NMR analysis. Fig. 5 shows the decrement of signal at 1802 cm -1 corresponding to some unreacted carbonated groups. It was also noticeable new absorption bands at 1720 cm -1 and 1647 cm -1 , which are typical for urethane and amide groups [START_REF] Nishikubo | Convenient syntheses of cyclic carbonates by new reaction of oxiranes with β-butyrolactone[END_REF]. The conversion of carbonated groups was also confirmed through 1 H-NMR (Fig. 6) through the disappearance of the cycliccarbonate signals at 4.22 ppm and 4.61 ppm. In the range of 4.8 -5.2 ppm, the broad signal is assigned to protons of NH and those in alpha position to the oxygen of the urethane function.

Protons in alpha to the nitrogen of this function arised at 3.16 ppm. The signal at 3.55 ppm is ascribed to protons in alpha position to hydroxyl groups. These correlations are in quite consistency with those of Tryznowski et al. [START_REF] Tryznowski | Facile route to multigram synthesis of environmentally friendly non-isocyanate polyurethanes[END_REF] and Meng et al. [START_REF] Meng | Investigation of non-isocyanate urethane functional latexes and carbon nanofiller/epoxy coatings[END_REF].

Kinetic model

In order to monitor the evolution of the reaction system in a quantitative way, samples were analyzed by FTIR spectroscopy during the reaction (Eqs (1-2)). These experimental data were used to estimate the kinetic constants of the production of urethane and amide groups.

Kinetics

Aminolysis reaction was considered as an elementary reaction. Amidation is a reversible reaction.

Thus, their kinetic rate equations were expressed as

𝑅 𝐴𝑚𝑖𝑛𝑜𝑙 = 𝑘 𝐴𝑚𝑖𝑛𝑜𝑙 × [𝐶𝑎𝑟𝑏𝑜𝑛𝑎𝑡𝑒𝑑][𝑛𝐵𝐴] (3)
𝑅 𝐴𝑚𝑖𝑑 = 𝑘 𝐴𝑚𝑖𝑑 × ([𝐸𝑠𝑡𝑒𝑟][𝑛𝐵𝐴] - [𝐴𝑚𝑖𝑑𝑒][𝑀𝑒𝑂𝐻] 𝐾 𝑐 ) (4)
where, RAminol and RAmid represent the reaction rate of aminolysis and amidation reaction, kAminol and kAmid stand for the kinetic constants of aminolysis and amidation reaction and [Carbonated],

[Ester], [nBA], and [Amide] are the concentrations of carbonated group, ester group, n-butyl amine, and amide group, respectively. Kc is the equilibrium constant for the amidation reaction.

The evolution of Kc can be expressed by a van't Hoff's law:

𝐾 𝑐 (𝑇 𝑅 ) = 𝐾 𝑐 (𝑇 Ref ) × 𝑒𝑥𝑝 ( -∆𝐻 𝑅,𝐴𝑚𝑖𝑑 𝑅 × ( 1 𝑇 𝑅 - 1 𝑇 Ref )) (5)
where, TR and TRef represent the reaction temperature and reference temperature and R is the universal gas constant and ∆𝐻 𝑅,𝐴𝑚𝑖𝑑 is the enthalpy of the amidation reaction, which was found to be -5.02 kJ.mol -1 from the calorimetry experiment. The equilibrium constants 𝐾 𝑐 was estimated at a reference temperature of 70 °C.

Mass Balance

A simplified scheme of the aminolysis is shown in Fig. 9. HERE Fig. 9. Aminolysis of carbonated methyl oleate.

The volumetric flow rate was constant during the addition time, thus, one gets

𝑑𝑉 𝑟 𝑑𝑡 = 𝑄 𝑓𝑒𝑒𝑑 for 𝑡 < t 𝑎𝑑𝑑 and 𝑑𝑉 𝑟 𝑑𝑡 = 0 L. s -1 for t > 𝑡 𝑎𝑑𝑑 (6)
where, Qfeed is the volumetric flow rate, tadd is the addition time and Vr is the volume of the reaction.

Ordinary differential equation 6 was used to simulate the evolution of the reactor volume.

Mass balance for all compounds in the reaction system can be expressed as:

𝑑[𝐶𝑎𝑟𝑏𝑜𝑛𝑎𝑡𝑒𝑑] 𝑑𝑡 = -𝑅 𝐴𝑚𝑖𝑛𝑜𝑙 -[𝐶𝑎𝑟𝑏𝑜𝑛𝑎𝑡𝑒𝑑] × 𝑄 𝑓𝑒𝑒𝑑 𝑉 𝑟 (7)
𝑑[𝑛𝐵𝐴] 𝑑𝑡 = -(𝑅 𝐴𝑚𝑖𝑛𝑜𝑙 + 𝑅 𝐴𝑚𝑖𝑑 ) + ([𝑛𝐵𝐴] 𝑓𝑒𝑒𝑑 -[𝑛𝐵𝐴]) × 𝑄 𝑓𝑒𝑒𝑑 𝑉 𝑟 (8)
𝑑[𝑈𝑀𝑂] 𝑑𝑡 = 𝑅 𝐴𝑚𝑖𝑛𝑜𝑙 -[𝑈𝑀𝑂] × 𝑄 𝑓𝑒𝑒𝑑 𝑉 𝑟 (9)
𝑑[𝐸𝑠𝑡𝑒𝑟] 𝑑𝑡 = -𝑅 𝐴𝑚𝑖𝑑 -[𝐸𝑠𝑡𝑒𝑟] × 𝑄 𝑓𝑒𝑒𝑑 𝑉 𝑟 (10)
𝑑[𝐴𝑚𝑖𝑑𝑒] 𝑑𝑡 = 𝑅 𝐴𝑚𝑖𝑑 -[𝐴𝑚𝑖𝑑𝑒] × 𝑄 𝑓𝑒𝑒𝑑 𝑉 𝑟 (11)
𝑑[𝑀𝑒𝑂𝐻] 𝑑𝑡 = 𝑅 𝐴𝑚𝑖𝑑 -[𝑀𝑒𝑂𝐻] × 𝑄 𝑓𝑒𝑒𝑑 𝑉 𝑟 (12)
where, [UMO] and [MeOH] are the concentration of urethanized methyl oleate and methanol, respectively.

Parameter estimation

For the estimation of the kinetic constants, the software MODEST was used [START_REF] Haario | MODEST-User's Guide[END_REF]. The ordinary differential equations ODEs [START_REF] Lligadas | Renewable Polyols for Polyurethane Synthesis via Thiol-ene/yne Couplings of Plant Oils[END_REF][START_REF] Kreye | Sustainable routes to polyurethane precursors[END_REF][START_REF] Maisonneuve | Isocyanate-Free Routes to Polyurethanes and Poly(hydroxy Urethane)s[END_REF][START_REF] Tomita | Polyaddition of bis(seven-membered cyclic carbonate) with diamines: A novel and efficient synthetic method for polyhydroxyurethanes[END_REF][START_REF] Del Rio | Biobased Polyurethanes from Polyether Polyols Obtained by Ionic-Coordinative Polymerization of Epoxidized Methyl Oleate[END_REF][START_REF] Ochiai | Branched cationic polyurethane prepared by polyaddition of chloromethylated five-membered cyclic carbonate and diethylenetriamine in molten salts[END_REF][START_REF] Deepa | Solvent-induced self-organization approach for polymeric architectures of micropores, hexagons and spheres based on polyurethanes prepared via novel melt transurethane methodology[END_REF] were solved out by the ODESSA algorithm based on backward difference methods.

Concentrations of ester and carbonated groups were used as observables. The objective function θ was minimized by the Simplex and Levenberg-Marquardt algorithms.

𝜃 = ∑(𝐶 𝑖 -𝐶 𝑖 ̂) (14)
where, Ci is the experimental concentration and 𝐶 𝑖 ̂ is the concentration simulated by the model.

To define the reliability of the model to the experimental data, the following coefficient of explanation was defined as

𝑅 2 = 1 - ∑(𝐶 𝑖 -𝐶 ̂𝑖) 2 ∑(𝐶 𝑖 -𝐶 ̅ 𝑖 ) 2 (15)
where, 𝐶 ̅ 𝑖 is the average value of the experimental concentration. The coefficient of explanation was higher than 90 %, which means that the model is correct.

To minimize the dependency between the activation energy and the pre-exponential factor, rate constants were expressed by using a modified Arrhenius equation.

𝑘 𝑖 (𝑇 𝑅 ) = 𝑘 𝑖 (𝑇 Ref ) × exp ( -𝐸 𝑎 𝑖 𝑅 ( 1 𝑇 𝑅 - 1 𝑇 Ref ) ) (16)
where, ki is reaction rate constant, Ea is the activation energy, TR represents the reaction temperature and reference temperature, R is the universal gas constant and TRef was fixed to 66.85 °C in our study.

Table 2 presents the values of the estimated parameters with associated standard deviations. The standard errors were estimated within 95 % of the confidence interval. One can notice that the standard deviations are low for the kinetic constants. For the equilibrium constant KC for the amidation reaction at 70 °C, the standard deviation is of 78 % due to the complexity to estimate such thermodynamic parameters. Nevertheless, this deviation is still acceptable.

HERE Table 2. Kinetic constants estimated at 66.85 °C and statistical data.

The results of the kinetic modeling are presented in Figs. 10a-10f. One can notice that the model fits correctly the experimental concentration of carbonated and ester groups. For the sake of information, the simulated concentrations of amide and urethane were also plotted. Figs. 11a-11b shows the contour plot for the estimated kinetic and activation energy constants for both reactions.

It is clear that the minimum of the objective function was reached.

Conclusion

The use of cyclic-carbonate such as carbonated vegetable oils and amine represents a greener and safer way for the production of non-isocyanate polyurethane. Several articles have discussed about this way of production but few of them have proposed a kinetic model. The goal of this article was to build a kinetic model for a model reaction: aminolysis of carbonated methyl oleate with nbutylamine.

In the first part of this study, the esterification and epoxidation steps were optimized to have the maximum yield in ester and epoxide groups. In the second part, several experiments of aminolysis were performed under isothermal mode in a semi-batch reactor. A Tian-Calvet calorimeter was used to determine the enthalpies of amidation and aminolysis reactions. It was found that these reactions are not very exothermic, i.e., ∆𝐻 𝑅,𝐴𝑚𝑖𝑑 = -5.02 kJ. mol -1 and ∆𝐻 𝑅,𝐴𝑚𝑖𝑛𝑜𝑙 = -18.92 kJ. mol -1 .

A kinetic model was built by taking into account the aminolysis reaction and the side reaction of amidation. A non-linear regression method was used to estimate the kinetic constants for these two reactions by using the experimental concentrations of ester and carbonated groups as observable.

The model fits quite well with the experimental concentrations.

In order to shift to industrial application, aminolysis of carbonated vegetable oils with diamines should be the continuation of this study.

Notation

FiguresFig. 1 .

 1 Figures

Fig. 2 .

 2 Fig. 2. Simplified reactor scheme for the epoxidation.

Fig. 3 .

 3 Fig. 3. Simplified reactor scheme for the carbonation.

Fig. 4 .

 4 Fig. 4. Reversal mixing cells of C80 calorimeter.

Fig. 5 .

 5 Fig. 5. FTIR-spectra for OA, MO, EMO, CMO and UMO.

Fig. 6 .

 6 Fig. 6. 1 H-NMR for OA, MO, EMO, CMO and UMO.

Fig. 7 .

 7 Fig. 7. Conversion of epoxidized methyl oleate to carbonated methyl oleate.

Fig. 9 .

 9 Fig. 9. Aminolysis of carbonated methyl oleate.

Fig. 10a .

 10a Fig. 10a. Fit of the model for the aminolysis of CMO at 40 °C and 4 mL.min -1 . Fig. 10b. Fit of the model for the aminolysis of CMO at 60 °C and 1mL.min -1 . Fig. 10c. Fit of the model for the aminolysis of CMO at 70 °C and 1mL.min -1 . Fig. 10d. Fit of the model for the aminolysis of CMO at 50 °C and 2 mL.min -1 . Fig. 10e. Fit of the model for the aminolysis of CMO at 50 °C and 4 mL.min -1 . Fig. 10f. Fit of the model for the aminolysis of CMO at 50 °C and 3 mL.min -1 .

Fig. 11b .

 11b Fig. 11b. Contour plot of kinetic parameters for the side reaction of amidation.

Table 1 .

 1 Experimental matrix.

	Amide	amide groups
	Carbonated	carbonated groups
	Carb	carbonation reaction
	Ester	ester group
	Ea	activation energy [kJ.mol -1 ]
	FTIR	fourier transform infrared spectroscopy
	1 H-NMR	proton nuclear magnetic resonance
	ΔHR	reaction enthalpy [kJ.mol -1 ]
	ki	reaction rate constant or kinetic constant [L.mol -1 .s -1 ]
	Kc	equilibrium constant
	MeOH	methanol
	Qfeed	volumetric flow rate [L⋅s -1 ]
	Ri	reaction rate [mol.L -1 .s -1 ]
	R	universal gas constant
	r	reaction rate for a reactant or product [mol.L -1 .s -1 ]
	T	temperature [K]
	tadd	addition time [s]
	Vr	volume of reaction [L]
	Ci	experimental concentration [mol.L -1 ]
	𝐶 𝑖 ̂	simulated concentration [mol.L -1 ]

Table 2 .

 2 Kinetic constants estimated at 66.85 °C and statistical data.

Acknowledgments

The authors thank the Ministry of High Education, Science and Technology of Dominican Republic. The authors thank the Maîtrise des Risques et Environnementaux department.

Calorimetry results

The evolution of the heat-flow rate as function of time is depicted in Fig. 8a. It stands for the overall energy released due to urethane formation and to amide formation at 60 °C. Fig. 8b shows the heat released only during the formation of urethanes at 60 °C. HERE Fig. 8.a Heat profiles for CMO and n-butylamine system at 60 °C. b. Heat profile for the production of urethanes at 60 °C.

By integrating the curves in Fig. 8a, the overall enthalpy of the reactional system (amidation + aminolysis) was found to be -23.90 kJ per mole of carbonated group. Then, the corresponding integration of heat-flow rate shown in Fig. 8b provides the enthalpy due to the formation of urethanes, which was found to be -18.92 kJ.mol -1 . Thus, the enthalpy of amidation is -5.02 kJ.mol -