Rachel Bocquet

Christian Le Bas

Caroline Mothe

Nicolas Poussing
email: nicolas.poussing@liser.lu

CSR, Innovation, and Firm Performance in Sluggish Growth Contexts: A Firm-Level Empirical Analysis

Keywords: CSR, Economic performance, Growth, Innovation

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Introduction

Corporate social responsibility (CSR) integrates ''social and environmental concerns to [firms'] business operations and in their interactions with stakeholders on a voluntary basis'' (Commission of the European Communities 2001, p. 6) and has, as one of its main benefits, the potential to drive innovation. For example, CSR strategies lead to enhanced technological innovation when integrated into firms' strategies [START_REF] Bocquet | Are firms with different CSR profiles equally innovative? An empirical analysis with survey data[END_REF], though empirical research offers contradictory results regarding their effects on financial performance [START_REF] Mcwilliams | Corporate social responsibility: A theory of the firm perspective[END_REF]. Some studies indicate a positive link [START_REF] Margolis | Misery loves companies: Rethinking social initiatives by business[END_REF]; others find a negative relationship (Go ¨ssling 2011). This lack of empirical consensus regarding the relationship between CSR and firm performance reflects a wide array of research issues [START_REF] Mcwilliams | Corporate social responsibility: Strategic implications[END_REF][START_REF] Perrini | Deconstructing the relationship between corporate social and financial performance[END_REF]. In particular, an overly strong emphasis on financial instead of economic performance and the use of different methods to measure social and economic performance [START_REF] Arlow | Social corporate structure and economic performance[END_REF][START_REF] Aupperle | An empirical examination of the relationship between corporate social responsibility and profitability[END_REF][START_REF] Cochran | Corporate social responsibility and financial performance[END_REF][START_REF] Orlitzky | Corporate social and financial performance: A meta-analysis[END_REF] represent important issues in prior empirical research. Many factors might influence the relationship between CSR and firm performance, such that intangible resources including innovation [START_REF] Surroca | Corporate responsibility and financial performance: The role of intangible resources[END_REF], reputation, and customer satisfaction [START_REF] Saeidi | How does corporate social responsibility contribute to firm financial performance? The mediating role of competitive advantage, reputation, and customer satisfaction[END_REF]) could be missing links that can help explain the relationship between CSR and financial performance more accurately.

In response to these research challenges, we analyze the effects of both CSR and technological innovation on firms' economic performance, measured as firm growth. This perspective has the advantage of addressing a mediumterm element of performance. Prior empirical literature already has established a positive effect of innovative implementations on the rhythm of firms' growth and validated Schumpeter's predictions (e.g., the recent survey by [START_REF] Colombelli | On firm growth and innovation: Some new empirical perspectives using French CIS (1992-2004)[END_REF]. But few studies address CSR and innovation together as determinants of firms' growth. By integrating them simultaneously, this study seeks a deeper understanding of the relationship among CSR, innovation, and firm growth. We here determine whether innovation influences the relationship between CSR and firm growth. From a foundation in literature that describes the link between CSR and firm performance, we enrich extant analyses by drawing on an evolutionary perspective. With this framework, we also consider how distinct CSR behaviors (strategic versus responsive) and differentiated innovation types (product, process, or both) can affect firm growth, thereby wondering whether the adoption of a CSR strategy necessarily leads to innovation, or whether certain types of CSR strategies are linked to certain types of innovation.

With data gathered from different surveys carried out in Luxemburg, we implement a two-step procedure that addresses several potential problems associated with introducing CSR and innovation concurrently. First, a probit model with instrumental variables enables us to analyze the effects of strategic versus responsive CSR behavior on technological innovation types (process, product, or both). Second, we introduce the predicted innovation variables in an ordinary least square (OLS) model, to measure the effects of innovation types on firm growth. We thus clarify the relationship among CSR, innovation, and firm growth, which has been neither conceptually recognized nor empirically captured by prior research. To the best of our knowledge, this study is the first to examine this relationship by considering both types of CSR behavior (strategic versus responsive) and types of technological innovation (process, product, or both).

The new insights into the relationship among CSR, innovation, and growth are particularly resonant for firms suffering sluggish growth. Whereas prior research often relies on data from periods when macroeconomic growth was consistent and persistent, many European economies continue to experience slow or sluggish growth, which affects not only their economic markets but also their firms' potential growth rate. 1 The persistent sluggishness (since 2007) shows few signs of changing, making it crucial to consider the focal relationships in a macro-context of demand stagnancy for European firms.

The rest of this article is organized as follows: ''Literature Survey and Hypothesis Development'' section provides an overview of previous research on the relationship between CSR and firm performance, as well as the potential influence of innovation in this relationship. ''Data and Methods'' section is devoted to the presentation of our data and empirical models. The data analyses and results follow in ''Results'' section. In ''Discussion and Conclusion'' section, we discuss the implications of our findings, some limitations, and avenues for further research.

Literature Survey and Hypothesis Development

CSR and Firm Performance: Is Innovation the Missing Link?

Growing literature deals with the economic consequences of corporate social responsibility (CSR) and its effects on financial performance. The results are sometimes contradictory [START_REF] Chassagnon | Towards a social ontology of the firm: Emergence, reconstitution, organisation, institution and power[END_REF]), yet most studies reveal a positive link (e.g., [START_REF] Margolis | Misery loves companies: Rethinking social initiatives by business[END_REF]cf. Go ¨ssling 2011), though to widely varying extents across studies [START_REF] Mcwilliams | Corporate social responsibility and financial performance: Correlation or misspecification?[END_REF][START_REF] Mcwilliams | Corporate social responsibility: Strategic implications[END_REF][START_REF] Orlitzky | Corporate social and financial performance: A meta-analysis[END_REF]. A key difficulty is that, unlike the measure of corporate social performance,2 no immediate measure exists for CSR. This difficulty becomes especially acute when the goal is to assess the impact of CSR on financial performance. Empirical research uses different accounting-or market-based measures [START_REF] Guiral | Corporate social performance, innovation intensity and financial performance: Evidence from lending decisions[END_REF]. As [START_REF] Tang | How corporate social responsibility engagement strategy moderates the CSR-financial performance relationship[END_REF] note, most studies also focus on defining exogenous factors that might affect the relationship of CSR with firm performance, such as the contexts in which a positive link becomes more robust. For example, [START_REF] Mcwilliams | Corporate social responsibility: A theory of the firm perspective[END_REF] posit that the lack of consensus across empirical studies reflects model specification problems, such as omitting R&D spending. They also hypothesize that R&D investments and CSR are highly correlated, because they both are associated with product and process innovation. Their results confirm this correlation; when R&D intensity appears in an equation, CSR has a neutral effect on profitability. Nor can we ignore co-evolution and loops between CSR and performance [START_REF] Preston | The corporate socialfinancial performance relationship[END_REF]. Go ¨ssling (2011) cites R&D and risk as important factors that influence the relationship between corporate social performance and financial performance.

A firm's innovation may play a role too [START_REF] Hull | Firm performance: The interactions of corporate social performance with innovation and industry differentiation[END_REF][START_REF] Surroca | Corporate responsibility and financial performance: The role of intangible resources[END_REF], such that if innovation is one of the independent variables, the CSR-financial performance relationship is no longer significant. [START_REF] Hull | Firm performance: The interactions of corporate social performance with innovation and industry differentiation[END_REF] explicitly address the potential moderating role of innovation in the CSR-financial performance relationship; they find that CSR most strongly affects the performance of low innovation firms. [START_REF] Surroca | Corporate responsibility and financial performance: The role of intangible resources[END_REF] demonstrate that intangible resources, including innovation, represent a missing link that can explain the relationships of CSR with financial performance. Although they find no direct relationship between CSR and financial performance, the indirect relationship relies on the mediating effect of a firm's intangible resources (innovation, human capital, reputation, and culture).

Beyond this mainstream view, some nascent literature seeks to describe how a firm might adopt different CSR engagement strategies to determine its financial performance. These strategies entail exogenous factors but also endogenous ones. For example, CSR engagement strategies based on certain organizational capabilities (e.g., absorptive capabilities, complementary resources) seemingly can maximize financial returns on CSR engagement (see [START_REF] Tang | How corporate social responsibility engagement strategy moderates the CSR-financial performance relationship[END_REF].

In turn, three main models have emerged to describe the relation between CSR and economic performance (Go ¨ssling 2011). Model 1, the ''charitable firm model,'' asserts that CSR induces no gains. Rather, CSR behavior is only costly, and firms do not expect any direct return. In Model 2, the ''legitimacy/commitment model'' (Go ¨ssling 2011), firms implementing CSR are more profitable (all else being equal) due to external factors, such as their better reputation [START_REF] Lourenc ¸o | The value relevance of reputation for sustainability leadership[END_REF], gains in legitimacy, and more market flexibility (''license to operate''), as well as internal factors such as human resources. In Model 3, the ''strategic CSR model'' [START_REF] Porter | The link between competitive advantage and corporate social responsibility[END_REF], CSR produces more business opportunities and innovations, enabling the firm to build competitive advantages (and more growth), through social progress. Such firms redesign products, markets, and productivity in the value chain. The model is anchored in a CSR-driven innovation or strategic CSR innovation approach.

Regarding the links between CSR and economic performance, [START_REF] Lankoski | Differential economic impacts of corporate responsibility issues[END_REF] also suggests that different corporate responsibility issues exert distinct economic impacts. Systematic patterns in these differences depend on whether the challenge is to reduce a negative externality or generate a positive externality, as well as whether the outcome benefits market or non-market stakeholders.

Relationship Among CSR, Innovation, and Firm Growth

Generally speaking, prior literature considers two types of firm performance indexes: financial or real. The former tend to rely on profitability indexes, such as the rates of return on assets or on equity. For example, a firm should choose an investment that maximizes the equity value criterion, because then it can accrue cash flows and distribute them to stockholders. Creating stockholder value is an increasingly adopted standard for business performance.

However, these financial indexes raise technical difficulties [START_REF] Oster | Modern competitive analysis[END_REF], even as they exhibit strong correlations with CSR performance [START_REF] Margolis | Misery loves companies: Rethinking social initiatives by business[END_REF]. That is, financial indexes indicate if the firm has allocated its tangible and intangible investments efficiently. In contrast, real performance indexes reveal if the firms have reached certain advantages over their competitors on a product market. As emphasized by evolutionary theory, firms' investment in knowledge capital is critical to their survival [START_REF] Nelson | Eurostat-OECD manual on business demography statistics[END_REF][START_REF] Penrose | The theory of the growth of the firm[END_REF]. For example, technological and non-technological innovations represent primary means to support firm performance, through productivity growth, as confirmed by multiple empirical studies in the tradition opened by [START_REF] Mansfield | Entry, Gibrat's law, innovation and the growth of firms[END_REF] and [START_REF] Griliches | R&D and productivity: Econometric results and measurement issues[END_REF]-which uses the Firm Technological Performance measure (FTP) as an indicator of firm performance. Sales growth is enhanced by the firm's ability to learn (e.g., [START_REF] Dess | Measuring organizational performance in the absence of objective measures: The case of the privately-held firm and conglomerate business unit[END_REF][START_REF] Tippins | IT competency and firm performance: Is organizational learning a missing link[END_REF]. It provides substantial advantages in implementation, because we do not need series of tangible capital to build the measure. Therefore, we focus on growth as a measure of firm (medium-to long-term) performance.

Furthermore, three main theoretical frameworks are available for studying the potential effect of innovation on firms' growth [START_REF] Colombelli | On firm growth and innovation: Some new empirical perspectives using French CIS (1992-2004)[END_REF]. The first stems from the well-known Gibrat's ''law of proportionate effects'' (1931), which indicates that firm size distributions are highly skewed, presumably following a log-normal function, so firm size follows a random walk. No deterministic factors explain differences in the extent of a firm's growth. A vast literature deals with the theoretical coherence and empirical relevance of this law (e.g., [START_REF] Cefis | Testing Gibrat's legacy: A Bayesian approach to study the growth of firms[END_REF], which also gained more attention following an application that showed that the rates of growth of large and/or old firms are often erratic and thus unpredictable [START_REF] Geroski | The growth of firms in theory and in practice[END_REF]. For such firms, there should be no deterministic impact of innovation activity on the scale of their growth. However, Gibrat's law is at odds with recent empirical studies that reveal the existence and persistence of heterogeneity in firms' performance [START_REF] Colombelli | The persistence of innovation and path dependence[END_REF].

A second firm growth model, proposed by [START_REF] Jovanovic | Selection and evolution of industry[END_REF], predicts disproportionate growth across firms on the basis of age, according to the inverse relationship between firm age and growth. This model reflects a neoclassical concept of firm-specific managerial efficiency (which can be interpreted in terms of human capital): Young firms do not know their efficiency level and learn through production experience. Some firms disappear, while others grow at a rate that decreases with age (for a given size) and with size (for a given age). Thus, younger firms grow faster than older firms [START_REF] Jovanovic | Selection and evolution of industry[END_REF]; see also [START_REF] Evans | Tests of alternative theories of firm growth[END_REF].

The third theoretical analysis of firm growth represents an evolutionary approach [START_REF] Nelson | Eurostat-OECD manual on business demography statistics[END_REF]. Firms competing in the same market face uneven production costs, due to differences in their technological capabilities. The differential growth rate across firms in the same sector therefore is a consequence of heterogeneity in their levels of efficiency (or capabilities). [START_REF] Cefis | A matter of life and death: Innovation and firm survival[END_REF], examining the effects of innovation on survival using data about Dutch manufacturing firms, show that firms benefit from an innovation premium that extends their life in the industry, independent of firm age or size. Process innovation in particular seems to have a distinctive effect on survival. [START_REF] Coad | Innovation and firm growth in high-tech sectors: A quantile regression approach[END_REF] find, with a large sample of high-tech firms, that growth may or may not relate to innovation activity (i.e., patenting), but innovation is more crucial for ''rapid growth'' firms. In the same vein, [START_REF] Cassia | Firms' growth: Does the innovation system matter?[END_REF] provide evidence that universities' knowledge input and output are important determinants of UK entrepreneurial firms' growth. According to [START_REF] Ernst | Patent applications and subsequent changes of performance: Evidence from time-series cross-section analyses on the firm level[END_REF], patent applications increase sales after a lag of 2 or 3 years, depending on the type of the patent system (national or European). That is, the effects of innovation on firm growth are not immediate but occur soon after an invention has been realized. [START_REF] Corsino | Product innovation and firm growth: Evidence from the integrated circuit industry[END_REF] use new, unique data pertaining to semiconductor devices commercialized during 1998-2004 around the world; at the corporate level, the most recent innovations significantly affect growth. At the business unit level, the influence of product innovations on business unit growth is even greater than that recorded at the corporate level. [START_REF] Demirel | The evolution of firm growth dynamics in the US pharmaceutical industry[END_REF] study pharmaceutical firms between 1950 and 2008 and observe that the positive impact of R&D on firm growth is conditional on a combination of firm-specific characteristics, such as firm size, patenting, and persistence in patenting. [START_REF] Colombelli | On firm growth and innovation: Some new empirical perspectives using French CIS (1992-2004)[END_REF] instead merge three waves of the French Community Innovation Survey (CIS 1992(CIS -2004) and find that innovative firms (regardless of innovation type) grow more than non-innovative ones.

Among these frameworks, an evolutionary approach appears particularly well suited to study the complex relationship of CSR, innovation, and growth at the firm level. To the best of our knowledge, no previous study has dealt empirically with these relationships. Therefore, we draw on the evolutionary frame and consider five central phenomena [START_REF] Dosi | Sources, procedures, and microeconomic effects of innovation[END_REF]): (a) technological opportunities; (b) incentives to exploit those opportunities; (c) firm capabilities to achieve technological changes (including R&D capacity and a well-trained workforce); (d) organizational arrangements and mechanisms, which facilitate the search for and implementation of technological advances; and (e) appropriability conditions, to generate rents stemming from innovation. In line with a strategic CSR innovation approach (Model 3), we predict that CSR also has an indirect, positive impact on firm economic performance, through innovation.

Hypotheses on the Link Between CSR, Innovation, and Growth

Our main hypothesis is related to the fact that innovation is the missing link in studies analyzing the effect of CSR on firm performance (here approached through growth, see ''CSR and Firm Performance: Is Innovation the Missing Link?'' section. above). Moreover, in line with [START_REF] Burke | How corporate social responsibility pays off[END_REF], [START_REF] Porter | The link between competitive advantage and corporate social responsibility[END_REF], and [START_REF] Lankoski | Differential economic impacts of corporate responsibility issues[END_REF], we also suggest that different types of CSR (i.e., strategic versus responsive) exert distinct economic impacts. We thus assert that the type of CSR has to be considered when analyzing its effect on innovation.

First, we position ourselves in the strategic CSR framework [START_REF] Bocquet | Are firms with different CSR profiles equally innovative? An empirical analysis with survey data[END_REF][START_REF] Burke | How corporate social responsibility pays off[END_REF][START_REF] Mcwilliams | Corporate social responsibility and financial performance: Correlation or misspecification?[END_REF][START_REF] Porter | The link between competitive advantage and corporate social responsibility[END_REF] which establishes a strong link between the strategic CSR profile and innovation in terms of products and processes. We therefore distinguish the effects of two CSR profiles (strategic versus responsive) on innovation, in line with [START_REF] Burke | How corporate social responsibility pays off[END_REF] who explicitly introduce the strategic dimension of CSR as a means to understand the extent to which CSR leads to value creation. We thus posit:

H1 Strategic CSR has a positive effect on technological innovation.

Second, we have seen that the abundant literature on the impact of CSR on firm performance [START_REF] Perrini | Deconstructing the relationship between corporate social and financial performance[END_REF] has provided controversial results. One of the reasons may lie in the fact that if innovation is omitted, the CSR-performance relationship cannot be significant. Taking into account firm's innovation [START_REF] Hull | Firm performance: The interactions of corporate social performance with innovation and industry differentiation[END_REF][START_REF] Surroca | Corporate responsibility and financial performance: The role of intangible resources[END_REF]) may thus of critical importance when studying the link between CSR and performance (through growth). Numerous empirical studies have tested the impact of innovation on firm growth (for an exhaustive review of these studies, see [START_REF] Colombelli | On firm growth and innovation: Some new empirical perspectives using French CIS (1992-2004)[END_REF], mostly showing the positive and significant relationship. Considering, first, that innovation represents a missing link between CSR and growth, second, that innovation has a positive effect on growth, third, that CSR has to be of strategic in order to be related to innovation, we assume that:

H2 Strategic CSR has a positive effect on firms' growth through the mediating effect of technological innovation.

Data and Methods

Data

For our empirical analysis, we used data from three sources: two surveys conducted by the Luxembourg Institute of Socio-Economic Science (LISER): the Community Innovation Survey [CIS] and Corporate Social Responsibility Survey [CSR] and an administrative dataset (Structural Business Statistics, from the national institute for statistics and economic studies of the Grand Duchy of Luxembourg [STATEC]).

In Luxembourg, the 2008 CIS data were collected by LISER on behalf of STATEC, with the support of the European Commission (Eurostat), using face-to-face interviews among firms that had at least 10 employees (classified as 10-49 employees, 50-249 employees, or 250 employees or more). This mandatory survey achieved a response rate of 86.4 %. The final sample includes 615 firms. The second dataset reflected the results of a CSR survey carried out in Luxembourg in 2008 by LISER (for the scale items, see the Appendix). Similar to CIS 2008, firms with more than 10 employees, from all economic sectors, were included in this survey. Among the population of 3296 companies in the national business register provided by STATEC, we built a sample of 2511 firms with more than 50 employees, and we created a stratified random sampling procedure for firms with 10-49 employees. The data collection took place between mid-September and mid-December 2008, using a mailed questionnaire available in French or German (and English on request). We received 1144 valid responses (response rate: 45.5 %). The CSR survey collected 2008 data about firms' general characteristics and their integration of CSR into their corporate strategy, namely, whether the firm had adopted CSR in the period under observation (2006)(2007)(2008) or planned to adopt CSR activities in the subsequent 2 years. 3We merged the data from these two surveys. For the merged sample of 266 firms, we gathered data on firm turnover from STATEC, as a structural business statistic and in accordance with European Commission regulations. We deleted records if these turnover data were missing for 2007, 2008, or 2009 or if firms indicated they had no employees (94 firms removed). To assess firm growth accurately, we needed to exclude firms that had experimented with mergers and acquisitions, because these external growth measures could radically increase turnover, in the case of mergers, or decrease it if a firm were acquired by another firm. Because these effects (positive or negative) generally are substantial in volume, we assumed that an increase (decrease) in the number of employees that exceeded 20 % in 3 years was due to a merger (acquisition). 4 Because these firms represent outliers with regard to their growth, we removed them from the sample (44 observations removed). [START_REF] Mairesse | The importance of process and product innovation for productivity in French manufacturing and services industries[END_REF] call such removals of extreme values appropriate. Thus, we obtained a final sample of 213 enterprises. To ensure representative results, the data were weighted on the basis of the number of firms per sector and employee size classes.

In our sample, 42 % of firms employed 50-249 people, 39 % between 10-49, and 19 % more than 250 people. We distinguished manufacturing (mining and quarrying, manufacturing, electricity, and gas and water supply) from service (wholesale trade, transport, storage and communication, financial intermediation, computer and related activities, architectural and engineering activities, and technical testing and analysis) industries, which represented 56 and 44 % of firms, respectively. In terms of CSR behavior and innovation, only 27 % of firms had adopted CSR, and 14 % expected to implement CSR practices in the near future. More firms (52 %) had introduced one type (single innovators) of technological innovation (process or product), but less than 25 % had introduced both process and product innovations (complex innovators). Firms that had introduced new or significantly improved methods of manufacturing or producing goods or services (process innovation) represented 46 % of our sample, whereas firms that introduced new or significantly improved goods (product innovation) represented 45 %. The proportion of firms engaging in innovative activity was greater among firms that had adopted CSR (28/57 = 49 %) than among others (57/156 = 36.5 %). Table 1 provides the descriptive statistics related to CSR and innovation behavior.

Variables

Table 2 contains the definitions of all the study variables and descriptive statistics.

Dependent Variables

The main dependent variable is firm growth, our proxy for firms' economic performance [START_REF] Orlitzky | Corporate social and financial performance: A meta-analysis[END_REF][START_REF] Roberts | Determinants of corporate social responsibility disclosure: An application of stakeholder theory[END_REF][START_REF] Russo | A resource-based perspective on corporate environmental performance and profitability[END_REF]. We measured growth in turnover between 2007 and 2009 in two ways. First, we computed growth for the overall time period using the variation of firm turnover in real price (DVCA79). Second, we calculated an average growth rate, to account for likely evolution during the overall time period. This variable is simply the arithmetic mean of the two-period growth rate (MOYDVCA79). Luxemburg experienced a recession during the study period, such that the rate of variation in the gross national product was 6.6 % in 2007 but -0.8 % in 2008; 2009 was marked by a severe recession (-4.1 %). Over these 3 years, the national product trend was nearly flat. With respect to the firms in our sample, the average turnover growth rate for 2007-2009 reflected the overall national tendency (-0.02 %). The study period also was characterized by very slow growth (or even recessions) in European economies in general; for the Europe 15, for example, the rate of variation was -0.2 % during 2007-2011.

To assess the role of innovation in the relationship between CSR and firm growth, we considered a second set of dependent variables related to firm innovation. Four dummy variables measure the different types of technological innovation: INPCS if the firm introduces new or significantly improved methods of . By distinguishing between single and complex innovators, we account for the idea that a complex innovator that can achieve product and process innovations jointly has an advantage in terms of its potential for creativity and new ideas, compared with more specialized firms (product or process). Moreover, synergetic relations may exist between improvements to products and improvements to processes (Le Bas and Poussing 2014). The new knowledge generated by searching for product improvements might spill over to research projects that aim to improve processes, or vice versa. As a consequence, we expect a complex innovator to grow faster.

Independent Variables

According to [START_REF] Mattingly | Measurement of corporate social action: Discovering taxonomy in Kinder Lydenberg Domini ratings data[END_REF], classification methods are particularly useful to clarify the CSR constructs that researchers intend the data to measure. Using an exploratory factor analysis, they show that the operationalization of the Kinder Lydenburg Domini Ratings Data (KLD) along a single dimension combining positive and negative social actions fails to produce a valid measure of CSR and could hide countervailing effects of social actions on financial performance. They find four distinct classes of social actions (positive and negative) toward distinct stakeholders (technical and institutional). Here we do not use the KLD data. As a consequence, we cannot construct the same CSR classes as those recommended by [START_REF] Mattingly | Measurement of corporate social action: Discovering taxonomy in Kinder Lydenberg Domini ratings data[END_REF]. However, following their recommendation and in line with CSR engagement strategy literature [START_REF] Tang | How corporate social responsibility engagement strategy moderates the CSR-financial performance relationship[END_REF], we include two endogenous variables derived from a classification procedure that reflect firms' CSR profiles (strategic versus responsive). For [START_REF] Burke | How corporate social responsibility pays off[END_REF], strategic CSR leads to value creation but requires firm alignment along five dimensions (centrality, proactivity, voluntarism, visibility, specificity).

To determine which firms adopt strategic or responsive CSR profiles, we applied the method suggested by [START_REF] Bocquet | Are firms with different CSR profiles equally innovative? An empirical analysis with survey data[END_REF]. First, we operationalized CSR practices with nine variables, according to the five dimensions identified by [START_REF] Burke | How corporate social responsibility pays off[END_REF]. Second, we conducted a principal component analysis on the CSR variables, which resulted in two distinct clusters. Cluster 1 (strategic CSR) comprises intensive CSR adopters, in terms of the number and intensity of the various types of CSR practices they undertake. Their engagement in CSR is supported by clear economic objectives, defined at the firm level, and also requires various formalized practices that reflect the firm's ability to incorporate a stakeholder's objectives into its business operations. In cluster 2 (responsive CSR), firms instead are poor CSR adopters. They have not attained full CSR adoption, lack an asserted economic objective, do not clearly identify their stakeholders, and have not really succeeded in formalizing their CSR practices. We also introduce two dummy variables to account for firms that plan to adopt CSR or not (PLAN_CSR) and those that do not implement any CSR practices (NO_CSR).

We control for factors that explain innovation, to isolate the pure effect related to CSR behavior. As mentioned previously, we adopt an evolutionary perspective, in the belief that the probability of innovation depends on a mix of firm-specific characteristics and sector configurations [START_REF] Mairesse | Using innovation surveys for econometric analysis[END_REF][START_REF] Teece | Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy[END_REF]. For example, a strong knowledge base includes R&D capacity and a well-trained workforce [START_REF] Cohen | Innovation and learning: The two faces of R&D[END_REF]. In line with McWilliams andSiegel's (2000, 2001) recommendations, and recognizing R&D as an important driver of innovation [START_REF] Mairesse | The importance of R&D for innovation: A reassessment using French survey data[END_REF], we included an instrumental variable to reflect whether the firm undertakes internal R&D (RDIN). This variable meets two necessary conditions: relevance (i.e., correlated with the endogenous variable) and orthogonality (i.e., uncorrelated with the error term of the second equation).

Because R&D expenditures cannot always capture innovation efforts, especially by smaller firms or in service sectors, we also considered the proportion of employees with a higher education degree (EMPHI), which offers a good proxy of firm-level human capital dedicated to innovation. Another important, if controversial, driver is competitive intensity [START_REF] Covin | Pioneers and followers: competitive tactics, environment and firm growth[END_REF][START_REF] Ozsomer | What makes firms more innovative? A look at organizational and environmental factors[END_REF]. With the belief that intense competition may push all types of innovation, we included a dummy variable (MARCONC), equal to 1 when competition in the firm's market is very intense and 0 otherwise. This variable came directly from the CIS 2008. We also used the dummy variable WORLD to reflect a firm's export activity. Exports likely favor technological innovation, due to a ''learning by exporting'' effect that enhances both innovation and productivity [START_REF] Cassiman | Innovation and internationalization through exports[END_REF]. When the share of the firm's turnover due to exports is greater than its share of turnover earned within its home country, WORLD equals 1, and 0 otherwise. Size matters for innovation too (see [START_REF] Russo | A resource-based perspective on corporate environmental performance and profitability[END_REF][START_REF] Wagner | Corporate social performance and innovation with high social benefits: A quantitative analysis[END_REF], because large firms have more resources to invest in technological activities and exploit external opportunities [START_REF] Cohen | Empirical studies of innovative activity[END_REF]; they also tend to be better organized to protect their innovations and capture the associated rents [START_REF] Teece | Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy[END_REF]. We accounted for these effects with a size measure (SMALL: 10-49 employees, MEDIUM: 50-249 employees, LARGE: more than 249 employees, according to European classifications). In addition, studies of CSR and innovation often include the sector of activity (e.g., [START_REF] Gallego-Alvarez | Corporate social responsibility and innovation: A resource-based theory[END_REF]. We used an INDUS variable to control for the firm's sector of activity (manufacturing vs. services). In the group of regressors, we also included the implementation of organizational innovation, which may partially determine technological innovation [START_REF] Haned | Firm persistence in technological innovation: The relevance of organizational innovation[END_REF][START_REF] Bas | The differentiated impacts of organizational innovation practices on technological innovation persistence[END_REF][START_REF] Mothe | Complementarities in organizational innovation practices: Evidence from French industrial firms[END_REF]. Diverse organizational practices were aggregated as one variable, to represent the introduction of (at least) one new or significantly improved organizational practice (INORG).

Methods

We aim to measure the impact of innovation on the growth of the firm when it adopts CSR behaviors. A common method would place the two focal variables (innovation and CSR) on the right side of a growth rate equation. However, we know that there is a relationship between CSR and innovation [START_REF] Bocquet | Are firms with different CSR profiles equally innovative? An empirical analysis with survey data[END_REF], which could create an endogeneity bias between innovation and growth [START_REF] Mansfield | Entry, Gibrat's law, innovation and the growth of firms[END_REF]): If innovation improves the firm's market positions, more growth means that more resources should to be invested in innovation activities (see [START_REF] Colombelli | On firm growth and innovation: Some new empirical perspectives using French CIS (1992-2004)[END_REF]. The same caution holds for the relation between CSR and growth. In the same way that there is a virtuous loop of innovation, there is a virtuous loop of CSR. To overcome this potential endogeneity bias across the variables, we assess the impact of CSR on firm growth using a twostage model. In line with Cre ´pon et al. ( 1998) and [START_REF] Hashi | The impact of innovation activities on firm performance using a multi-stage model: Evidence from the community innovation survey 4[END_REF], we introduce the instrumental variables. In a first step, we assess the effects of the decision related to CSR on the propensity to innovate (with control variables), using four probit models for each type of innovation. In a second step, we note the relationship between technological innovation types and firm growth, by introducing the predicted innovation variables as explanatory variables in the model that explains the rate of variation in turnover. The model is an ordinary least square (OLS) specification, because turnover variation is a continuous variable. To obtain proper standard errors [START_REF] Guan | From the help desk: Bootstrapped standard errors[END_REF][START_REF] Stock | A survey of weak instruments and weak identification in generalized method of moments[END_REF], we used bootstrapping [START_REF] Camponovo | Robustness of bootstrap in instrumental variable regression[END_REF] and performed 3000 replications.

Results

The four models related to the determinants of innovation (see Table 3) show that firms implementing strategic CSR exhibit a higher probability to innovate in their process (Model 3) and in both process and product (Model 4). In contrast, there is no significant impact on product or process innovation (Model 1) or on pure product innovation (Model 2). These results partially validate H1. In addition, responsive CSR behavior has a significant negative effect on the probability of introducing all types of innovation, in line with previous results that suggest responsive CSR constitutes a barrier to innovation [START_REF] Bocquet | Are firms with different CSR profiles equally innovative? An empirical analysis with survey data[END_REF]). When we avoid the type of CSR and consider only whether the firm undertakes CSR, this last variable has no significant effect. Analyzing CSR by the type of CSR chosen by the firm thus adds value to the model.

With respect to the effects of the control variables, the factors linked to the firm's knowledge base (RDIN, EMPHI) are significantly positive, as expected. However, internal R&D activity has no effect in Models 3 and 4. The coefficients for competition exhibit the expected signs, except for in the product innovation model [START_REF] Cabagnols | The determinants of the type of innovative behaviour at the firm level[END_REF]. Small firms have a lower propensity to innovate in process and to be complex innovators. The sector variable is significantly positive. Also as hypothesized, firms implementing organizational innovation exhibit a higher probability of being technological innovators.

In the OLS estimation for the second step (see Table 4) related to the link with growth, the innovation variable is a predicted variable, derived from the first step in the estimated model, so that it accounts for the likely effect of CSR. The four models (5-8) show that technological innovation, whatever its type, always has positive impacts on firm growth5 (at 10 %). This result corroborates H2. Two other aspects deserve attention. The effects of the predicted probabilities to implement process innovation (Model 7) and to implement both process and product innovations (Model 8) on growth are greater than the effects of the predicted probability to implement product innovation (Model 6) and to implement product or process innovations (Model 5). This result is consistent with the growth rate definition and in line with recent literature (e.g., [START_REF] Colombelli | On firm growth and innovation: Some new empirical perspectives using French CIS (1992-2004)[END_REF]. [START_REF] Pianta | Innovation and employment[END_REF] reveals that process innovation strategies are associated with price competitiveness, whereas product innovation strategies are linked to technological competitiveness (technological leadership). Therefore, cost-reducing process innovations can increase the level of demand for products in the current period and result in higher growth. The effect of technological competitiveness on growth instead is less immediate. [START_REF] Coad | Processes of firm growth and diversification: theory and evidence[END_REF] show that the timing of the economic effects of product innovation is complex, and [START_REF] Mairesse | Innovation and productivity: A firmlevel analysis for French manufacturing and services using CIS3 and CIS4 data (1998-2000 and 2002-2004[END_REF] reveal a similar result derived from French CIS data: Process innovation is the main determinant of labor productivity (and there is no effect of product innovation). When an important share of the firm's turnover comes from exports to global markets (dummy WORLD), the growth rate is significantly lower. This result is coherent with the depression that affected the world economy after the financial crisis of 2008. We posit that firms with important foreign markets were more affected by this worldwide recession.

Discussion and Conclusion

In this article, we have examined the relationship between CSR and firm performance by explicitly accounting for the often neglected effect of innovation [START_REF] Luo | Corporate social responsibility, customer satisfaction, and market value[END_REF][START_REF] Surroca | Corporate responsibility and financial performance: The role of intangible resources[END_REF]. Unlike previous studies that focus on financial performance, we consider firm growth as a measure of medium-term economic performance. This approach enables us to address a fundamental trait of firms, namely, their capacity to be durably viable in their competitive environments. Combining strategic management theory of CSR and the evolutionary approach of growth, our findings confirm that innovation has a significant role in determining the relationship between CSR and firm growth. Indeed, innovation influences this relationship but only when firms adopt an asserted strategic CSR behavior. In contrast, firms that adopt responsive CSR behaviors face counterproductive, negative consequences.

We contribute to prior literature by revealing two sides of CSR through innovation. In line with Luo and Bhattacharya 2006), our results show that previous research has been somewhat overly enthusiastic about the positive benefits of CSR; it has also a ''dark side'' that generates negative outcomes. These authors attribute the negative returns to a tradeoff between investments in CSR versus the firm's core competencies, such as innovation, which should receive higher strategic priority than CSR initiatives. They also note that firms that are less innovative in meeting stakeholders' needs may send a negative signal of incorrect or opportunistic strategic choices that degrades their legitimacy and performance. In contrast, highly innovative firms can generate positive market value from CSR, given that their stakeholders' needs have been successfully satisfied. In a more recent contribution, [START_REF] Luo | The debate over doing good: Corporate social performance, strategic marketing levers, and firm-idiosyncratic risk[END_REF] also show that the simultaneous pursuit of CSR, advertising, and R&D may be financially detrimental, because it increases firm idiosyncratic risk. They caution that pursuing all these strategic goals simultaneously is difficult, if not impossible, because most firms experience resource limits. We provide further evidence of the ''dark side'' of CSR but argue it is more a question of the context in which firms pursue their strategic goals than of goal quantity. This dark side of CSR should lead to negative effects on performance, but we find instead that it has direct negative consequences only for innovation, probably due to the insights provided by our twostep model. In particular, the costs of CSR may be lower than its benefits, depending on the type of CSR strategy (responsive versus strategic), which affects a firm's innovation. That innovation in turn generates different economic returns to CSR. Our study reveals not only the role of innovation in the relationship between CSR and firm growth but also the conditions that lead to a potential trade-off between innovation and CSR initiatives. A responsive CSR strategy has negative impacts on the propensity to undertake various types of technological innovations; strategic CSR behavior favors innovative probability (in process and in both process and product). Therefore, firms that have fully integrated CSR into their business strategies perform better in terms of innovation and economic performance. In particular, process and complex innovators that benefit from strategic CSR experience more growth. These results support the conjecture suggested by [START_REF] Porter | The link between competitive advantage and corporate social responsibility[END_REF] regarding the potential value creation related to strategic CSR. They explicitly argue that firms linking CSR and innovation create synergetic effects and generate greater innovation and growth. Our findings confirm the need ''to consider proactive management as an instrument that enables organizations to maintain dynamic alignment with their general business environment'' (Ortiz Avram and Khu ¨ne 2008, p. 3) to innovate and thus generate higher economic returns from CSR. [START_REF] Tang | How corporate social responsibility engagement strategy moderates the CSR-financial performance relationship[END_REF] show that a firm's CSR engagement strategy (pace, consistency, relatedness, and path) affects the effectiveness of CSR implementation. Along similar lines, our findings confirm that the manner in which a firm engages in CSR can significantly affect the benefits generated from its engagement. The fine measures of the two CRS strategies and their differentiated effects indicate that consistent engagement may yield different results.

With respect to the impact on firm growth, our results are weakly significant. They might be subject to a limitation, in the sense that the time period in which we calculated growth was characterized by quasi-stagnation in the country under observation (Luxemburg) and for many of the firms in our sample. To what extent did this phenomenon affect our results? Garcia-Quevedo et al. (2014), performing a growth analysis for UK firms during the same time period, show that the lack of trust in the macro-conditions of demand prevented firms from engaging in innovative activities. The macroeconomic context in the Europe 15 nations strongly altered the conditions associated with tracking firm growth drivers. It also increased the difficulty of finding determinants of firm growth, by blurring the causal links among CSR, innovation, and growth.

This study is subject to several further limitations. First, we only tested the effect of innovation on the CSR-firm performance link. Other intangible resources that might mediate or moderate this relationship should be included together in future empirical studies. Second, we used a strategic measure of CSR to distinguish two firm profiles (responsive versus strategic). This approach had the virtue of reflecting whether the firm had integrated all CSR components (environmental, social, business) into its strategic vision or not. However, an interesting extension could test for the existence of complementarity or substitution effects across CSR components [START_REF] Cavaco | CSR and financial performance: Complementarity between environmental, social and business behaviours[END_REF]. Third, the size of the sample represents a limitation. An in-depth analysis of innovations' complementarity would be more feasible with a larger sample. Fourth, other non-technological innovations, such as marketing, organizational, or business model innovations, might have effects. Fifth, researchers might consider a direct effect of CSR on firm growth, beyond the indirect effect through firm innovative behaviors. Sixth, adding another 3-year time period would provide a means to test for the effects of CSR and innovation in a more longitudinal way, providing some possible explanations of the causal effects. It also would ensure a lag between the dependent variable and the regressors, which could produce more significant coefficients and effects.

From a managerial perspective, this study confirms the importance of CSR as a strategy that favors innovation and firm growth. Moreover, it specifies that all CSR strategies do not lead to the same benefits; the outcome depends on their implementation. Strategic CSR, because it ensures the dynamic alignment of CSR activities with the firm's general business strategy, is likely to meet stakeholders' medium-term expectations. Managers who are keen to implement CSR initiatives therefore should incorporate this strategic dimension. Otherwise, they could be penalized, in terms of both their innovation and their economic returns.

Table 1

 1 Firm CSR and innovation behavior

		Don't	Innovate in product	Innovate	Innovate	Total (1 ? 2)
		innovate (1)	or process (2)	in process	in product
	Adopt CSR	29	28	5	22	57
	Don't adopt CSR	99	57	39	46	156
	Total	128	85	44	68	213
	Table 2 Variables and descriptive statistics (n = 213)
	Variable	Definition			Mean (Std. Deviation) Min	Max
	(acronym)
	MOYDVCA79 Average growth between 2007 and 2009 using the arithmetic mean of the two-	-0.0005226 (0.23379) -0.4202 2.7751
		period rate of growth in real price (continuous variable)
	DVCA79	Growth between 2007 and 2009 using the variation of firm turnover in real price	-0.02216 (0.43011) -0.6789 5.1170
		(continuous variable)
	INPCS	Process innovation: the firm introduces new or significantly improved methods	0.46543 (0.46543)	0	1
		of manufacturing or producing goods or services (dummy variable)
	INPDT	Product innovation: the firm introduces new or significantly improved goods	0.45539 (0.49918)	0	1
		(dummy variable)
	INNO	Process innovation or product innovation (dummy variable)		0.52112 (0.50073)	0	1
	COMPLEX	Process innovation and product innovation		0.24882 (0.43335)	0	1
	CSR	Firms with CSR practices (dummy variable)		0.26760 (0.44375)	0	1
	STRATEGIC	Firms with strategic CSR profiles (dummy variable)		0.10798 (0.31109)	0	1
	RESPONSIVE Firms with responsive CSR profiles (dummy variable)		0.15962 (0.36712)	0	1
	PLAN_CSR	Firms plan to adopt CSR (dummy variable)		0.14084 (0.34868)	0	1
	NO_CSR	Firms don't adopt and don't plan to adopt CSR (dummy variable)		0.59154 (0.49271)	0	1
	RDIN	The firm undertakes internal R&D activity		0.26760 (0.44375)	0	1
	EMPHI	Percentage of employees with higher education (incl. post-secondary college and	0.25489 (0.30430)	0	1
		university) (dummy variable)
	MARCONC	The competition of the market is very intense (dummy variable)		0.58216 (0.49437)	0	1
	SMALL	Total number of employees is 10-49 (dummy variable)		0.38967 (0.48882)	0	1
	MEDIUM	Total number of employees is 50-249 (Dummy variable)		0.417840 (0.49437)	0	1
	LARGE	Total number of employees is more than 249 (dummy variable)		0.19248 (0.39518)	0	1
	INORG	Organizational innovation: the firm introduces a new organizational method into	0.54930 (0.49874)	0	1
		its business practices (incl. knowledge management), workplace organization,
		or external relations (dummy variable)
	INDUS	Belongs to the manufacturing sector (dummy variable)		0.44131 (0.49771)	0	1
	WORLD	Most of the firm's turnover between 2006 and 2008 comes from outside the	0.525822 (0.50051)	0	1
		domestic market (dummy variable)

Table 3

 3 Probit model: determinants of the probability to innovate Determinants of firm growth (OLS)

	First step: correction of endogeneity bias
		Model 1	Model 2	Model 3	Model 4
		INNO	INPDT	INPCS	COMPLEX
	STRATEGIC	0.03157 (0.15326)	0.12053 (0.14924)	0.77318*** (0.14086)	0.91070*** (0.14431)
	RESPONSIVE	-0.96686*** (0.13334)	-0.65336*** (0.12962)	-0.86916*** (0.14062)	-0.55682*** (0.14138)
	PLAN_CSR	0.13159 (0.14089)	0.26811* (0.14162)	0.07973 (0.14502)	0.28895* (0.15202)
	NO_CSR	Ref.	Ref.	Ref.	Ref.
	INORG	1.28339*** (0.09114)	1.13301*** (0.09145)	1.21264*** (0.09652)	1.20766*** (0.10700)
	RDIN	2.46347*** (0.24552)	2.25908*** (0.19331)	-0.05188 (0.11244)	0.09851 (0.11308)
	EMPHI	0.69792*** (0.13637)	0.99522*** (0.13542)	0.68231*** (0.13476)	1.00331*** (0.13858)
	MARCONC	0.07284 (0.08594)	0.20641** (0.08754)	0.15502* (0.08352)	0.28405*** (0.08909)
	SMALL	-0.13254 (0.10524)	-0.02979 (0.10695)	-0.50736*** (0.09964)	-0.45480*** (0.10461)
	MEDIUM	Ref.	Ref.	Ref.	Ref.
	LARGE	-0.13959 (0.23260)	-0.20435 (0.22462)	-0.19789 (0.17974)	-0.23067 (0.18373)
	INDUS	0.32344*** (0.10479)	-0.09660 (0.11040)	0.66105*** (0.10020)	0.33680*** (0.11008)
	INTERCEPT	-1.13699*** (0.13621)	-1.43601*** (0.14036)	-1.38325*** (0.13732)	-1.81413*** (0.15208)
	Pseudo R 2	0.3452	0.3523	0.2320	0.2549
	Log likelihood	-646.75145	-630.12602	-672.47296	-605.87269
	Number of observations	213	213	213	213
	Significant effects are in bold
	Standard error in brackets. See Table 2 for the variable definitions
	Second step: correction of the endogeneity bias
		Model 5	Model 6	Model 7	Model 8
		MOYDVCA79	MOYDVCA79	MOYDVCA79	MOYDVCA79
	INNO_PREDICT	0.10692* (0.06078)	0.10492* (0.06116)	0.15610* (0.08329)	0.13892* (0.08149)
	INDUS	0.02479 (0.02766)	0.03650 (0.02820)	0.01678 (0.02659)	0.03418 (0.02840)
	SMALL	0.02799 (0.04025)	0.02570 (0.04071)	0.04654 (0.04280)	0.03977 (0.04234)
	MEDIUM	REF.	REF	REF.	REF.
	LARGE	0.05797 (0.04930)	0.05438 (0.05018)	0.07827* (0.04761)	0.07034 (0.04720)
	WORLD	-0.13529*** (0.03918)	-0.13594*** (0.03948)	-0.13477*** (0.03911)	-0.13416*** (0.03946)
	INTERCEPT	-0.04226 (0.03717)	-0.03671 (0.03580)	-0.05231 (0.04756)	-0.03949 (0.04391)
	Adjusted R 2	0.1518	0.1504	0.1519	0.1450
	Number of observations	213	213	213	213
	Significant effects are in bold
	Standard error in brackets. See Table 2 for the variable definitions
	*** Significant at 1 %; ** Significant at 5 %; * Significant at 10 %

*** Significant at 1 %; ** Significant at 5 %; * Significant at 10 % Table

4

[START_REF] Garcı ´a-Quevedo | Reviving demand-pull perspectives: The effect of demand uncertainty and stagnancy on R&D strategy[END_REF] show, with a panel of Spanish firms, that deteriorated demand conditions have strong negative effects on R&D investments.

Corporate social performance is more directly applicable (see Go ¨ssling 2011), and different measures of it have been suggested, including investment in pollution control equipment, treatment of women and minorities, or relations with customers[START_REF] Waddock | The corporate social performancefinancial performance link[END_REF].

The harmonized survey questionnaire is available at http://ec. europa.eu/eurostat/documents/203647/203701/CIS_Survey_form_ 2008.pdf/e06a4c11-7535-4003-8e00-143228e1b308 (Last access June 2015).

The 20 % threshold reflects the quantile distribution of firms according to their number of employees. This characteristic concerns in particular the very specific population of high-growth firms. According to the OECD (2007), high-growth firms are those with at least 10 employees that achieve average annualized growth greater than 20 % over a 3-year period, measured by employment levels or employee turnover. In line with[START_REF] Schreyer | High-growth firms and employment[END_REF], small firms are particularly focused on their higher job creation and job destruction rates. In our dataset, 43 of the 44 removed firms employed 10-249 people. These high-growth firms need to be removed, because their growth predominantly comes from external sources, such as mergers and acquisitions[START_REF] Picard | Les gazelles en France[END_REF]).

We obtained similar results when we measured growth as the variation of firm turnover in real prices (DVCA79).


Jennifer A Melanson

Carlotta Figliola

Deborah A Smithen

Aleksandra K Kajetanowicz

Alison Thompson
email: alison.thompson@dal.ca

Probing the Hydrolytic Reactivity of 2-Difluoromethyl Pyrroles

-Difluoromethyl pyrroles were found to be stable while N-protected with an electronwithdrawing group. Due to the propensity of pyrroles to access azafulvenium-like intermediates, the C-F bonds of an -difluoromethyl substituent are labile under hydrolytic conditions. The presence of certain electron-withdrawing substituents about the pyrrolic ring can accelerate this process, as determined through a kinetic comparison of the deprotection and subsequent hydrolysis reactions of Nprotected -aryl -difluoromethyl pyrroles.

Introduction

Porphyrinogens have been intensely studied, particularly as regards to chemical and biological relevance of the corresponding porphyrins. [1][2][3][4] Although spontaneous oxidation of porphyrinogens to porphyrins can render the isolation of these precursors rather challenging, 5 calix [4]pyrroles 6 bear eight alkyl or aryl groups at the meso positions of the tetrapyrrolic skeleton and thus resist oxidation. [7][8][9][10][11][12][13][14] The presence of a meso sp 3 carbon confers to the structure a significant conformational freedom, 5 enabling potential binding of these macrocycles for a wide range of applications. [7][8][9][10][11][12][13][14] As part of an ongoing effort to develop functionalised dipyrrolic structures, we began to investigate the synthesis of pyrroles featuring a -CF 2 -moiety at the α-position, contrasting with the -CR 2 -unit (R = alkyl or aryl) used as precursors to calix [4]pyrroles. The strength of the C-F bond, 15 alongside its ability to sterically mimic the C-H unit, has driven growing interest in the use of fluorine as an isostere of hydrogen, a common strategy in agrochemical 16 and pharmaceutical industries. 17,18 In tandem, the development of more efficient and diverse methods through which to incorporate this functional moiety, either directly [19][20][21][22] or via the fluorination of existing functionality, 23 renders this group even more suitable for incorporation into a wide variety of frameworks. However, there are few reports describing pyrroles bearing a difluoromethyl substituent directly appended to the heterocyclic core. Baran and co-workers developed a fluorinating reagent for the installation of a difluoromethyl group on nitrogen-containing heteroaromatic compounds via a radical mechanism (Scheme 1, top): 19 N-unsubstituted 2-and 3-acyl pyrroles 1a-b were shown to react promptly with ZnDFMS in the presence of tBuOOH and gave the αdifluoromethyl-substituted analogues 2a-b in moderate yield. Note that 2a and 2b both feature conjugated electron-withdrawing acyl groups that serve to stabilise the heterocylic core.

Scheme 1. Examples of α-difluoromethyl-substituted pyrroles.

In 1995 Scott reported the fluorination of several 2-formyl pyrroles using DAST, with the goal of synthesising an inhibitor of the uroporphyrinogen III cosynthase. 24 Pyrrole 3, which features a substitution pattern matching that of the enzyme substrate, uroporphomethene, reacted with DAST to render 4 in high yield (87%, Scheme 1, middle). Subsequent deprotection of 4 under standard hydrolysis conditions was reported to give the desired α-difluoromethyl pyrrole 5 apparently without loss of fluorine. However, experimental conditions or isolated yields for this step are not described, nor does the report include any evidence for the stated maintenance of fluoro substituents. As reported by Haufe (Scheme 1, bottom), 25 upon exposure to acid the stability of the difluoromethyl group is strongly influenced by the electronic nature of ring substitution. Indeed, in the presence of the electron-donating methyl group the difluoromethyl group was hydrolysed to the corresponding 2-formyl pyrrole 6a, while, under the same reaction conditions, pyrrole 6b was reported to be stable (Scheme 1). With the backdrop of these limited reports, we report herein upon the reactivity of -difluoromethyl pyrroles under hydrolytic conditions, 24 as well as an approach for the preparation of β-aryl--difluoromethyl pyrroles. Furthermore, the influence of the pyrrolic ring substitution pattern upon the reactivity of the -difluoromethyl functional group is discussed.

N H R 1 R 2 N H R 1 R 2 CF 2 H 2a : 55% 2b : 65% 1a : R 1 = COMe, R 2 = H 1b : R 1 = H, R 2 =

Results and discussion

The procedure for the synthesis of pyrrole 5 was repeated according to Scott's method (Scheme 1, middle). 24 However, upon N-deprotection of 4 the isolated product corresponded to the N-unprotected aldehyde 8 (75%, Scheme 2), with the two pendant esters of course hydrolysed to the corresponding carboxylic acids. As this result clearly contradicts the literature report, 24 the reaction was repeated in deuterated solvents and progress was followed via 1 H and 19 F NMR spectroscopic analysis. The initial N-deprotection of the -difluoromethyl pyrrole 4 was determined to occur immediately upon addition of 2 M NaOH. The N-deprotected product 5 is unstable under these reaction conditions, forming first the -dimethylacetal pyrrole 7 which then hydrolyses to the -formyl pyrrole 8 (Scheme 2 and Figure 1 in the Supplementary Information). In order to exclude the possibility that the two alkanoate moieties influence the hydrolytic reactivity of the -difluoromethyl group, the unsubstituted variant 10 was exposed to the same conditions. 26 Xtalfluor-M ® was used to fluorinate the 2-formyl pyrrole 9, giving the α-difluoromethyl pyrrole 10 in high yield (90%, Scheme 3). The use of a stabilising N-protecting group proved essential for the fluorination reaction to be successful. To study the N-deprotection, aliquots from the reaction of 10 with 2 M aqueous NaOH in MeOD at 50 C were analysed using 1 H and 19 F NMR spectroscopy. As observed previously for 4, the rapid appearance of the N-unprotected material 11 was followed by methoxide displacement of the fluoro substituents, to give the acetal 12, which hydrolysed to the aldehyde 13 (Scheme 3 and Figure 2 in Supporting Information).

Scheme 2. N-deprotection and hydrolysis of pyrrole bearing a 2-difluoromethyl group.

Scheme 3: Formation and hydrolysis of -difluoromethyl pyrrole 11.

Although some N-unprotected -difluoromethyl pyrroles featuring electron-withdrawing substituents on the heterocycle are stable (Scheme 1), 19 such systems are clearly different to pyrroles such as 5 and 11, whereupon hydrolysis to result in loss of fluorine is facile. In order to investigate the influence of the electronic properties of substituents about the pyrrolic ring upon the deprotection and hydrolysis reactions, a series of N-(2-nosyl)-β-aryl-substituted pyrroles were synthesised. Moving away from the tosyl and -SO 2 Ph protecting groups, the 2-nosyl group was selected thus enabling the Ndeprotection to be monitored via release of 2-nitrophenyl phenyl sulfide (14, Scheme 4). 27,28 13, R = CHO nitrophenyl or 2,4-dinitrophenyl phenyl sulfides. Furthermore, although 2-nitrophenyl phenyl sulfide is known, [29][30][31] full characterisation proved elusive in the literature. Compound 14 was, therefore, prepared via deprotection of 15 using PhSH and NEt 3 . The ejected sulfide 14 was isolated in quantitative yield (Scheme 4), thereby demonstrating that this anhydrous method is viable for the needed N-deprotection of N-(2-nosyl) pyrroles. 27,28,32 The absorption maximum of 14 occurs at 368 nm (CH 3 CN), with an extinction coefficient of 4000 L mol -1 cm -1 . Upon N-deprotection of pyrroles 19a-e with PhSH and NEt 3 under anhydrous conditions, the resulting pyrroles (22a-e) proved to be stable providing the material remained under an inert and anhydrous environment (Scheme 5). As such, the deprotection and subsequent hydrolysis reaction could be studied separately. The first step was studied using UV-Vis spectroscopy under pseudo-first order conditions using 400 equivalents of PhSH and 560 equivalents of NEt 3 in CH 3 CN at 0 C under an inert atmosphere. Despite maintaining a steady flow of nitrogen gas in the sample chamber of the spectrophotometer, the presence of phenyl disulfide (17 in Scheme 4) was noted upon careful inspection of the reaction mixture arising from the N-deprotection of 19a-e. Several pathways to 17 may be at play during the reaction, e.g. thiophenol affords disulfide in the presence of an oxidising agent and a base; 33,34 the reaction by-product sulfur dioxide 18 acts as an oxidising agent. As the disulfide 17 also absorbs at 368 nm, the absorbance reading at this 35 wavelength is representative of both products. Since the interference from 17 is constant across the sample set, the relative production of 14 (Table 1, in Supporting Information) represents a qualitative estimation of the N-deprotection rate (Table 1). The starting materials provide no interference at the monitoring wavelength. The production of 14 was monitored via its absorbance at 368 nm (Table 1 in Supporting Information), and the relative rate constants of deprotection were thus calculated:

As shown in Table 1, the presence of electron-withdrawing character in the aryl substituent causes an increase in the rate of N-deprotection (19a, R = CF 3 ). In contrast, electron-donating character (19e, R = OCH 3 ) impedes the reaction rate. Fig. 1 shows a Hammett reaction constant (ρ) of 0.4, suggesting an increase of negative charge in the reaction intermediates. These features support the reaction mechanism proposed in Scheme 6. After nucleophilic attack by PhSH, 37,38 the Meisenheimer-type intermediate 23 presumably collapses to give the reaction intermediate 24 and the development of anionic character in the orthogonal p-orbital of the pyrrolide nitrogen atom. 27 The ability of the substituent (R) within the aryl group to stabilise the transition state leading to 24 thus plays an important role in the rate of deprotection. Indeed, electron-withdrawing groups serve to stabilize the forming pyrrolide anion, thereby enhancing the reaction rate, yet electronwithdrawing groups serve to destabilise the transition state en route to 24. As the electron-donating and electron-withdrawing R substituents are somewhat distant from the developing anionic nitrogen atom, their effects in stabilising the transition state are small and thus the ρ value (Fig. 1) is small. Having determined successful N-deprotection conditions, attention was turned to the hydrolysis of the -difluoromethyl group. Hydrolysis was monitored using 19 F NMR spectroscopy under pseudo first-order conditions. Pyrroles 19 were first N-deprotected in an NMR tube using 1.8 equivalents of PhSH and 2.5 equivalents of NEt 3 , dissolved in CD 3 CN. Subsequently, hydrolysis was initiated through the injection of 1000 equivalents of water at 40 C. As the hydrolysis reaction progressed, the decreasing intensity of the 19 F doublet arising from the -CF 2 H group, with respect to the inert internal standard (hexafluorobenzene, 0.5 equiv., 0.4 M solution in CD 3 CN), was measured and the rates of hydrolysis calculated ( Although the variation in the rates of hydrolysis are subtle, the Hammett plot ( Based on these results, and the concave up parabola of the Hammet plot, two competing reaction pathways are proposed for the hydrolysis of 22 (Scheme 7). In the case of R being an electrondonating group (R = CH 3 and OCH 3 ), the rate-determining step is considered to be the loss of fluoride and formation of the positively charged azafulvenium intermediate 25, whose methylene carbon atom is activated towards the fast addition of water and the return of aromaticity to the pyrrole ring in 26. [41][42][43][44] After proton loss the intermediate 27 would collapse into the isolated aldehyde 29, again through loss of fluoride via azafulvenium formation. In the case of R being an electron-withdrawing group (R = CF 3 , F and CN) the generation of 25 would be slow, as appreciated upon consideration of the resonance contributor In this case, loss of a proton, to form negatively charged pyrrolide 30, is proposed as the rate-determining step. The transition state en route to 30 would be stabilised by electron-withdrawing substituents on the aryl ring. Loss of fluoride would then generate the azaulvene 32, followed by addition of water to give 33. Proton exchange would provide 27, which would collapse into the isolated aldehyde 29, presumably again via initial pyrrolide formation and subsequent generation of the corresponding azafulvene. Akin to the N-deprotection step, as the electron-donating and electronwithdrawing substituents (R) are somewhat distant from the developing azafulvenium and pyrrolide cores, their effects in stabilising the transition states are small and consistent with the small ρ values (Fig. 1) for the two constituent slopes of the concave up parabola.

Scheme 7. Proposed mechanisms for the hydrolysis of 22.

To summarise, the tendency for -difluoromethyl pyrroles to react with water is significant, particularly in the absence of significant electron-withdrawing N-protection. As such, the electronic nature of substituents about -difluoromethyl pyrroles influences the reactivity, and hence the stability, of the -difluoromethyl group. Driven by azafulvenium formation, the loss of fluoride is facile, 41 yet a significant electron-donating character on the pyrrolic ring serves to make azafulvenium character (via loss of fluoride) less favourable. In these cases, hydrolysis is proposed to rely upon N-deprotonation, followed by azafulvene formation via loss of fluoride. Therefore, the design of air-stable difluoromethyl pyrroles must consider the incorporation and positioning? of units with significant pyrrole stabilising ability, [42][43][44] and/or electron-withdrawing capacity via N-protection, in order to avoid hydrolysis.

-F CHO R N H F OH EWG N F OH 2 F H CF 2 H CF 2 H F H F OH 2 -H EWG N F OH 2 EWG CF 2 H N H 29
Comment re acyl?

Experimental

General information

All 1 H and 13 C NMR spectra were obtained using a 500 MHz NMR spectrometer (operating at 500 MHz and 125 MHz, respectively) and CDCl 3 as solvent. Chemical shifts were recorded in parts per million (ppm) with internal reference to CDCl 3 ( 1 H NMR at 7.26 ppm, 13 C NMR at 77.16 ppm) and to (CD 3 ) 2 CO ( 1 H NMR at 2.05 ppm, 13 C NMR at 29.84 and 206.26 ppm). 19 F NMR spectra were obtained using a 500 MHz NMR instrument (operating at 470 MHz) using trifluoroacetic acid (TFA, 19 F NMR at -76.55 ppm vrs. CFCl 3 ). Splitting patterns are indicated as follows: a, apparent, br, broad; s, singlet; d, doublet; t, triplet; q, quartet; m, multiplet. Coupling constants (J) are reported in units of Hertz (Hz).

High and low resolution ESI+ mass spectra were recorded using ion trap instruments. Column chromatography was performed using 230-400 mesh ultrapure silica. TLC was performed using silica gel or neutral aluminum oxide plates and were visualised using UV light (254 nm) and/or developed with vanillin stain. UV analysis was carried out with the baseline manually corrected for the solvent used. Moisture-sensitive reactions were performed in flame-dried glassware under a positive pressure of nitrogen. Solutions of air-and moisture-sensitive compounds were introduced via syringe or cannula through a rubber septum. Compounds 4, 45 9, 46 and 15 47 were prepared according to literature procedures.

3-(4-(Carboxymethyl)-5-formyl-1H-pyrrol-3-yl)propanoic acid (8)

Compound 4 45 (0.050 g, 0.120 mmol) was added to a solution of 1M NaOH in 1:1 H 2 O/MeOH (1 mL).

The reaction mixture was heated to 50 ºC until TLC analysis showed complete consumption of the starting material. The reaction mixture was diluted with H 2 O (50 mL) and acidified to pH 4 by use of 2M aq. HCl at 0 ºC. The reaction mixture was then extracted with CH 2 Cl 2 (3 x 50 mL), and the combined organic fractions were washed with brine, dried over anhydrous Na 2 SO 4 , concentrated in vacuo and purified via column chromatography (50% EtOAc/hexanes). The title compound was isolated as a white solid (0.012 g, 27% yield). 1

General Procedure (GP1) for Fluorination using XtalFluor ®

XtalFluor-E ® (3 equiv) or XtalFluor-M ® (3 equiv) was added, as indicated, to a solution of NEt 3 •3HF (4 equiv) and NEt 3 (2 equiv) in 1,2-DCE [0. 3 M], with stirring at room temperature under N 2 atmosphere at 70 ºC. The 2-formylpyrrole substrate (1 equiv) was then added in one portion and the reaction mixture was stirred under N 2 at room temperature overnight, before quenching with sat. aqueous NaHCO 3 (10 mL) and then stirring for 15 minutes. The reaction mixture was then diluted with CH 2 Cl 2 (30 mL) and washed with H 2 O (30 mL) and brine (30 mL). The organic phase was dried over anhydrous Na 2 SO 4 , concentrated in vacuo and purified via column chromatography.

2-(Difluoromethyl)-1-(phenylsulfonyl)-pyrrole (10)

Using GP1 and XtalFluor-M ® with gentle heating (35 ºC) in CH 2 Cl 2 , the title compound was synthesised from 1-(phenylsulfonyl)-pyrrole-2-carbaldehyde (9) 46 (0.13 g, 0.57 mmol). The title compound was isolated as a white solid (0.13 g, 92% yield) after column chromatography (10% Et 2 O/hexanes). M.p.: 64-66 °C; 1 H NMR (CDCl 3 , 500 MHz): δ 7.89 (d, 2H, J = 8.0 Hz), 7.63 (t, 1H, J = 8.0 Hz), 7.53 (t, 2H, J = 8.0 Hz), 7.32 (br s, 1H), 7.12 (t, 1H, J HF = 55 Hz, CF 2 H), 6.66 (br s, 1H), 6.31 (at, 1H, J = 1.8 Hz) ppm; 19

2-(Difluoromethyl)-1-(2-nitrophenylsulfonyl)-4-(4-(trifluoromethyl)phenyl)-pyrrole (19a)

Using GP1 and XtalFluor-M ® , the title compound was synthesised from 21a (0.32 g, 0.75 mmol). The title compound was isolated as a beige solid (0.29 g, 85% yield) after column chromatography (50% CH 2 Cl 2 /hexanes). M.p.: 80-81 °C; 1

2-(Difluoromethyl)-4-(4-fluorophenyl)-1-(2-nitrophenylsulfonyl)-pyrrole (19b)

Using GP1 and Xtalfluor-E ® , the title compound was synthesised from 21b (0.29 g, 0.78 mmol). The title compound was isolated as a beige solid (0.19 g, 61% yield) after column chromatography (50% CH 2 Cl 2 /hexanes). M.p.: 86-88 °C; 1

2-(Difluoromethyl)-1-(2-nitrophenylsulfonyl)-4-phenyl-1H-pyrrole (19c)

Using GP1 and Xtalfluor-E ® , the title compound was synthesised from 21c (0.23 g, 0.65 mmol). The title compound was isolated as a beige solid (0.22 g, 90% yield) after column chromatography (50% CH 2 Cl 2 /hexanes). M.p.: 100-103 °C; 1

2-(Difluoromethyl)-1-(2-nitrophenylsulfonyl)-4-p-tolyl-1H-pyrrole (19d)

Using GP1 and Xtalfluor-E ® , the title compound was synthesised from 21d (0.24 g, 0.65 mmol). The title compound was isolated as a beige solid (0.18 g, 70% yield) after column chromatography (50% CH 2 Cl 2 /hexanes). M.p.: 114-115 °C; 1

2-(Difluoromethyl)-4-(4-methoxyphenyl)-1-(2-nitrophenylsulfonyl)-1H-pyrrole (19e)

Using GP1 and Xtalfluor-E ® , the title compound was synthesised from 21e (0.30 g, 0.78 mmol). The title compound was isolated as a beige solid (0.20 g, 62% yield) after column chromatography (50% CH 2 Cl 2 /hexanes). M.p.: 145-148 °C; 1

2-(Difluoromethyl)-4-(4-cyanophenyl)-1-(2-nitrophenylsulfonyl)-1H-pyrrole (19f)

Using GP1 and Xtalfluor-E ® , the title compound was synthesised from 21f (0.13 g, 0.33 mmol). The title compound was isolated as a beige solid (0.12 g, 86% yield) after column chromatography (90% aqueous layer was extracted with CH 2 Cl 2 (equivalent volume to aqueous layer x 3). The combined organic layers were dried over Na 2 SO 4 , filtered, concentrated in vacuo and then purified via column chromatography.

1-(2-Nitrophenylsulfonyl)-4-(4-(trifluoromethyl)phenyl)-pyrrole-2-carbaldehyde (21a)

Using GP2 and 4-(trifluoromethyl)phenylboronic acid, the title compound was synthesised from 20 (0.50 g, 1.39 mmol). The title compound was isolated as an off-white solid (0.36 g, 62% yield) after column chromatography (CH 2 Cl 2 ). M.p.: 187-189 °C; 1

4-(4-Fluorophenyl)-1-(2-nitrophenylsulfonyl)-pyrrole-2-carbaldehyde (21b)

Using GP2 and 4-fluorophenylboronic acid, the title compound was synthesised from 20 (0.50 g, 1.39 mmol). The title compound was isolated as an off-white solid (0.45 g, 86% yield) after column chromatography (CH 2 Cl 2 ). M.p.: 172-175 °C; 1

Scheme 4 .Scheme 5 :

 45 Scheme 4. Synthesis of 2-nitrophenyl phenyl sulfide 14.

Fig. 1

 1 Fig. 1 Hammett plot for N-deprotection of 19a-e.

Scheme 6 :

 6 Scheme 6: Proposed mechanism for the N-deprotection of 19.

  Fig 2) resembles a concave up parabola with a minimum at R = H (22c). To confirm the concave up parabola, we synthesized and analysed 22f (R = CN), following the same protocols as previously, and were delighted to observe an excellent fit with the data generated from 22a-22e. The non-linear relationship39,40 revealed on the Hammet plot points to the influence of the electronic features of the substituents on the aryl ring of pyrroles 22. The ρ value for electron-donating groups was found to be -0.4, suggesting a build-up of positive charge (or neutralisation of negative charge, negative slope,Fig 2). In contrast, the ρ value for electron-withdrawing groups was found to be 0.4, suggesting an increase of the negative charge character in the transition state of the rate-determining step (positive slope,Fig 2).

Fig 2

 2 Fig 2 Hammett plot for the hydrolysis of 19a-f following N-deprotection.

13 C

 13 H (300 MHz, C(O)(CD 3 ) 2 ): δ 10.81 (br s, 1H), 9.70 (s, 1H), 7.07 (as, 1H), 3.85 (s, 2H), 2.78 (t, J = 8.0 Hz, expected 2H but overlaps with water peak), 2.59 (t, J = 8.0 Hz, 2H) ppm; HRMS-ESI (m/z): [M + Na] + Calcd 248.0529 for C 10 H 11 NNaO 5 ; found 248.0528. NMR is not reported because of the instability of 8 in CDCl 3 , C(O)(CD 3 ) 2 , and CD 3 OD for prolonged periods of time and its insolubility in THF-d8 and CD 3 CN.

( 2 -

 2 F NMR (CDCl 3 , 470 MHz) δ -110.8 (d, J FH = 55.0 Hz, CF 2 H) ppm; 13 C{ 1 H} NMR (CDCl 3 , 125 MHz): δ 138.6, 134.5, 129.6, 127.9, 127.4, 125.1 (t, J CF = 3.0 Hz), 115.6 (t, J CF = 5.0 Hz), 112.2, 108.9 (t, J CF = 233 Hz, CF 2 H) ppm; HRMS-ESI (m/z): [M + Na] + calcd 280.0214 for C 11 H 9 F 2 NNaO 2 S; found 280.0201. Nitrophenyl)(phenyl) sulfide (14) A solution of PhSH (0.30 mL, 3.21 mmol) and 1-(2-nitrophenylsulfonyl)-1H-pyrrole-2-carbaldehyde (15) 47 (0.50 g, 1.78 mmol) in anhydrous CH 3 CN (89 mL) was bubbled with N 2 for 10 minutes, after which anhydrous NEt 3 (0.62 mL, 4.46 mmol) was added under N 2 . The reaction mixture was stirred for 30 minutes before the solvent was removed in vacuo. The crude residue was then dissolved in CH 2 Cl 2 (200 mL) and washed with brine (200 mL). The organic layer was dried over Na 2 SO 4 , concentrated in vacuo and purified via column chromatography (05% EtOAc/CH 2 Cl 2 ). The title compound was isolated as a yellow solid (0.41 g, quant.). M.p.: 69-70 °C; 1 H (500 MHz, CDCl 3 ): δ 8.21 (d, 1H, J = 8.0 Hz), 7.59-7.51 (m, 2H), 7.50-7.46 (m, 3H), 7.33 (t, 1H, J = 8.0 Hz), 7.21 (t, 1H, J = 8.0 Hz), 6.87 (d, 1H, J = 8.0 Hz), comparable to previously reported data; 48 13 C{ 1 H}: NMR (CDCl 3 , 125 MHz): δ 145.2, 139.5, 136.0, 133.5, 131.2, 130.2, 130.1, 128.5, 125.8, 125.1 ppm; HRMS-ESI (m/z): [M + Na] + calcd 254.0246 for C 12 H 9 NNaO 2 S; found 254.0239; ε 368 nm = 4000 L mol -1 cm -1 in CH 3 CN.

  H NMR (CDCl 3 , 500 MHz): δ 7.88 (ad, 1H), 7.80-7.84 (m, 1H), 7.71-7.76 (m, 3H), 7.64-7.67 (m, 4H), 7.09 (s, 1H), 7.08 (t, 1H, J HF = 55 Hz, CF 2 H) ppm; 19 F NMR (CDCl 3 , 470 MHz) δ -63.7 (s), -113.1 (d, J FH = 55 Hz, CF 2 H) ppm; 13 C{ 1 H} NMR (CDCl 3 , 125 MHz): δ 147.9, 135.8, 135.6, 133.1, 132.5, 130.3, 129.8 (q, J CF = 27 Hz), 126.3 (q, J CF = 256 Hz, CF 3 ), 126.2 (aq, J CF = 3.0 Hz), 126.1, 125.5, 122.6, 114.3 (t, J CF = 5.0 Hz), 108.7 (t, J CF = 235 Hz, CF 2 H) ppm, two carbon signals missing; HRMS-ESI (m/z): [M + Na] + calcd 469.0257 for C 18 H 11 F 5 N 2 NaO 4 S; found 469.0241.

  H NMR (CDCl 3 , 500 MHz): δ 7.88 (d, 1H, J = 8.0 Hz), 7.80 (t, 1H, J = 8.0 Hz), 7.71 (t, 1H, J = 8.0 Hz), 7.63 (d, 1H, J = 8.0 Hz), 7.59 (d, 1H, J = 1.8 Hz), 7.49-7.52 (m, 2H), 7.09 (t, 2H, J = 9.0 Hz), 7.06 (t, 1H, J HF = 55 Hz, CF 2 H), 7.02 (s, 1H) ppm; 19 F NMR (CDCl 3 , 470 MHz) δ -113.0 (d, J FH = 55 Hz, CF 2 H), -(115.0-115.1) (m) ppm; 13 C{ 1 H} NMR (CDCl 3 , 125 MHz): δ 162.6 (d, J CF = 248 Hz, CF), 147.8, 135.4, 133.1, 132.8, 130.0, 129.4, 128.3 (d, J CF = 3.0 Hz), 127.6 (d, J CF = 8.0 Hz), 126.8, 125.4, 121.4, 116.1 (d, J CF = 22 Hz), 114.6 (t, J CF = 5.0 Hz), 108.8 (t, J CF = 235 Hz, CF 2 H) ppm; HRMS-ESI (m/z): [M + Na] + calcd 419.0289 for C 17 H 11 F 3 N 2 NaO 4 S; found 419.0287.

  H NMR (CDCl 3 , 500 MHz): δ 7.88 (d, 1H J = 8.0 Hz), 7.78 (t, 1H, J = 8.0 Hz), 7.69 (t, 1H, J = 8.0 Hz), 7.56 (d, 1H, J = 1.8 Hz), 7.53 (d, 1H, J = 8.0 Hz), 7.46 (d, 2H, J = 9.0 Hz), 7.07 (t, 1H, J HF = 55 Hz, CF 2 H), 7.03 (s, 1H), 6.94 (d, 2H, J = 9.0 Hz), 3.84 (s, 3H) ppm; 19 F NMR (CDCl 3 , 470 MHz) δ -113.0 (d, J FH = 55 Hz, CF 2 H) ppm; 13 C{ 1 H}: NMR (CDCl 3 , 125 MHz): δ 159.6, 147.7, 135.2, 133.1, 129.6, 129.3, 129.1, 127.5, 127.1, 125.4, 124.7, 120.7, 114.7 (t, J CF = 5.0 Hz), 114.6, 108.8 (t, J CF = 235 Hz, CF 2 H), 55.5 ppm; HRMS-ESI (m/z): [M + Na] + calcd 431.0489 for C 18 H 14 F 2 N 2 NaO 5 S; found 431.0491.

  H NMR (CDCl 3 , 500 MHz): δ 9.70 (s, 1H), 8.56-8.60 (m, 1H), 8.03 (s, 1H), 7.85-7.88 (m, 3H), 7.68-7.72 (m, 4H), 7.49 (d, 1H, J = 2.0 Hz) ppm; 19 F NMR (CDCl 3 , 470 MHz) δ -62.6 (s) ppm; 13 C{ 1 H} NMR (CDCl 3 , 125 MHz): δ 177.3, 176.9, 148.3, 135.9, 135.4, 134.2, 133.9, 132.6, 131.2, 130.1 (q, J CF = 33 Hz), 128.3, 126.3 (q, J CF = 270 Hz, CF 3 ), 126.2 (ad J CF = 3.5 Hz), 126.2, 125.8, 125.3 ppm; HRMS-ESI (m/z): [M + Na] + calcd 447.0238 for C 18 H 11 F 3 N 2 NaO 5 S; found 447.0235.

  H NMR (CDCl 3 , 500 MHz): δ 9.68 (s, 1H), 8.51-8.53 (m, 1H), 7.90 (s, 1H), 7.83-7.85 (m, 3H), 7.53-7.55 (m, 2H), 7.42 (d, 1H, J = 2.0 Hz), 7.12 (t, 2H, J = 9.0 Hz) ppm; 19 F NMR (CDCl 3 , 470 MHz) δ -(113.6-113.7) (m) ppm; 13 C{ 1 H} NMR (CDCl 3 , 125 MHz): δ 177.6, 162.8 (d, J CF = 248 Hz, CF), 135.7, 134.1, 133.7, 132.6, 131.4, 129.6, 128.0 (d, J CF = 3.0 Hz), 127.7 (d, J CF = 8.0 Hz), 127.5, 126.8, 126.0, 125.2, 116.3 (d, J CF = 22 Hz); HRMS-ESI (m/z): [M + Na] + Calcd 397.0270 for C 17 H 11 FN 2 NaO 5 S; found 397.0271.

Table 1 . Relative rate constants and Hammett parameters for the deprotection of 19a-e.

 1 rate constants calculated on two replicates of each substrate using Kaleidagraph v 4.1.3 and error on replicates calculated using XLSTAT v 2015.4.01.21576; b as reported36

					Hammett
	Compound	Substituent (R)	[Starting Material] (M)	Rate Constants (s -1 ) a	Substituent Constants
					(σ b )
	19a 19b	CF 3 F	4.03×10 -4 4.11×10 -4	(1.96 ± 0.01) ×10 -2 (1.23 ± 0.04) ×10 -2	0.54 0.06	0.19 -0.01
	19c	H	4.08×10 -4	(1.24 ± 0.08) ×10 -2	0	0.000
	19d 19e	CH 3 OCH 3	4.15×10 -4 3.57×10 -4	(1.19 ± 0.03) ×10 -2 (0.81 ± 0.02) ×10 -2	-0.17 -0.27	-0.02 -0.19

a

Table 2 )

 2 . The disappearance of the -CF 2 H group signal in each case was accompanied by the expected appearance of the HF singlet, which derives from hydrolysis of the -CF 2 H group (Figure3-7 in the Supporting Information).

	R			R
				PhSH
		N	CF 2 H	NEt 3 , MeCN	N	CF 2 H
		SO 2			H
			NO 2		22
	SH	19
	R			R
				-SO 2
		N	CF 2 H		N	CF 2 H
	PhS H	SO 2	NO 2	SPh	24
				NO 2
		23		14

Table 2 . Rates and Hammett parameters for the hydrolysis of 22a-f.

 2

					Hammett
	Compound	Substituent (R)	[Starting Material] M	Rate Constant (s -1 ) a	Substituent Constants
					(σ b )
	22a 22b	CF 3 F	1.400×10 -2 1.408×10 -2	(1.712 ± 0.092) ×10 -3 (0.966 ± 0.108) ×10 -3	0.54 0.06	0.27 0.02
	22c	H	1.501×10 -2	(0.914 ± 0.094) ×10 -3	0.00	0.00
	22d 22e 22f	CH 3 OCH 3 CN	1.422×10 -2 1.450×10 -2 1.488×10 -2	(1.021 ± 0.013) ×10 -3 (1.195 ± 0.025) ×10 -3 (1.749 ± 0.040) ×10 -3	-0.17 -0.27 0.66	0.05 0.12 0.28
		a rate constants calculated using Kaleidagraph v 4.1.3 and error is calculated using
			XLSTAT v 2015.4.01.21576; b as reported 36

  F NMR (CDCl 3 , 470 MHz) δ -113.0 (d, J FH = 55 Hz, CF 2 H) ppm; 13 C{ 1 H} NMR (CDCl 3 , 125 MHz): δ 137.9, 135.2, 133.1, 129.8, 129.7, 129.3, 129.2, 127.8, 125.8, 125.4, 121.3, 114.7 (t, J CF = 5.0 Hz), 108.8 (t, J CF = 235 Hz, CF 2 H), 21.3 ppm, two carbon signals missing; HRMS-ESI (m/z): [M + Na] + calcd 415.0540 for C 18 H 14 F 2 N 2 NaO 4 S; found 415.0522.

	H NMR (CDCl 3 , 500 MHz): δ 7.88 (d, 1H, J = 8.0 Hz), 7.78 (t,
	1H, J = 8.0 Hz). 7.69 (t, 1H, J = 8.0 Hz), 7.61 (d, 1H, J = 1.8 Hz), 7.53 (d, 1H, J = 8.0 Hz), 7.43 (d, 2H,
	J = 8.0 Hz), 7.21 (d, 2H, J = 8.0 Hz), 7.06 (s, 1H), 7.06 (t, 1H, J HF = 55 Hz, CF 2 H), 2.37 (s, 3H) ppm;

19

Acknowledgments

This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Nova Scotia Health Research Foundation (NSHRF). The authors thank Professor Norman P. Schepp (Dalhousie University) for assistance as regards to determining rates of reaction.

Notes and references

(1) Lash, T. D.; Mani, U. N.; Drinan, M. A.; Zhen, C.; Hall, T.; Jones, M. A. J. Org. Chem 1999, 64, 464.

Data regarding rates of reaction; copies of NMR spectra. See DOI: XXX

AUTHOR INFORMATION Corresponding Author

*E-mail: Alison.Thompson@dal.ca