dataesr/scientific-paragraphs-categorization huggingface dataset:
Dick-Nielsen, Feldhütter, and Lando (  2012 ) also look at the subprime crisis and arrive at basically the same conclusion, but they use a novel approach: they proxy liquidity as an equally weighted sum of four (normalized) measures of liquidity and liquidity risk (the Amihud measure of price impact, a measure of roundtrip trading costs, and the variabilities of these two measures). Another set of studies examines how processes and relations within a company affect its bond liquidity. Lee and Cho (2016) , using a dataset of 959 corporate bonds traded in Korea between 2003 and 2007, first demonstrate (in line with most of the existing literature) that issue size and age are the most important determinants of bond liquidity. More interestingly, using corporate governance evaluation scores from the Korea Corporate Governance Service, the authors conclude that better corporate governance increases the liquidity of corporate bonds, enabling companies to lower their debt transaction costs by improving transparency and reducing information asymmetry.
Green bond data Because there was no widely accepted definition of "green" between 2007, the first climate bond issuance, and 2014, the publication of the Green Bond Principles from the International Capital Market Association (ICMA), the definition of a "green" asset or project has depended on the issuer's and investor's visions. Therefore, for around 7 years, it was impossible to build a commonly accepted green bond database. Still today, most market participants build their own green bonds databases. Indeed, institutional investors and large commercial banks that underwrite green bond issuances have pioneered the collection and exploitation of green bond data. In Section 3. 4, we provide details about our sample selection process.
Liquidity data A bond is initially issued on the primary market, where issuers (corporations, financial institutions, governments) sell it to an investor who becomes the first holder. Afterwards, a bond can be bought and sold on the secondary market by any investor until it reaches its maturity. A bond's liquidity is then defined as the facility with which it is buyable or sellable on the secondary market. To measure this liquidity we use the bid-ask spread (BAS; see Section 2. 3).
Sample selection process We construct our database by combining private access databases 3  and free online databases. Our initial sample consisted of 3174 green bonds. From this initial sample, we removed all duplicates, identifying them through their ISIN codes. We then excluded securities (bank facilities and bank loans; commercial papers; private placements; green asset-backed securities; mortgage-backed securities) and sustainability bonds whose proceeds were to be used for both green and social purposes (as such dual-purpose bonds do not fit internationally recognized definitions of green bonds). Finally, we excluded issuances for which we lacked financial information. These filters reduced the database from 3174 to 2079 green bond issuances. Because our full sample of green bonds is partly composed of small issuances and unquoted bonds whose liquidity is null or not calculable, we considered additional filters.
We dropped bonds issued by governmental institutions and selected those issued by publicly listed financial and nonfinancial firms. 4 We then matched the resulting sample of green bond issuers with issuer-level annual accounting information obtained from Compustat North America and Compustat Global. We also merged our resulting green bonds sample with manually collected monthly readability data as well as monthly liquidity data retrieved from Bloomberg. Finally, we excluded observations with missing values for any variable used in this study. Our final sample contains 3057 monthly observations corresponding to 274 green bonds issued by 102 unique firms across 23 countries during the period 2011-2018. Table  1  compares the cross-country distributions of the initial green bonds sample and our final sample.
Empirical Source Data Our study is based on 'replication logic' and 'cross-case comparative analysis', as adopted by the researchers of the five empirical source studies from which we obtained our data (for details see Appendix 1). Our empirical source data were comprised of sets of behavioural categories/statements (BSs) of effective and ineffective managerial performance that had resulted from these CIT managerial behaviour studies conducted within public hospitals in Egypt, Mexico, Romania, and the UK, respectively. When briefing the CIT informants who participated in each study: Effective Managerial Performance was defined as: behaviour which you would wish all managers/leaders to adopt if and when faced with similar circumstances or situations; and Ineffective Managerial Performance was defined as: behaviour which, if it occurred repeatedly or even once in certain circumstances, might cause you to begin to question or doubt the ability of that particular manager/leader in that instance.
Data Analysis The units of analysis were the deduced sets of BSs obtained from the five empirical source studies. Author 1 independently subjected these to a three-stage inductive coding and categorization process  (37)  conducted at a semantic level of analysis. The first stage involved open coding to identify the salient units of meaning of each BS (i. e. 1 st -order concepts). The second stage involved axial coding to identify those BSs that were the same as, similar to, or contained an element of congruent meaning with one or more other BSs; these were then grouped into discrete behavioural categories (BCs) (i. e. 2 nd -order concepts). For a BC to be considered nation-general and potentially universalistic, it had to be underpinned by BSs from at least one of the two 'Western' and two of the three 'non-Western' BS data sets.
Research Methods and Processes The theoretical foundation guiding the empirical source studies, which also informs our present multiple cross-case/cross-nation comparative study, relied on the Multiple Constituency Model of Organizational Effectiveness (see  Tsui (1990)  and Implicit Leadership Theory  (Eden and Leviatan, 1975). Adopting a common research aim, design and data collection/analysis protocol, the subject focus of all five studies (cases) was on senior, middle and first-line managers/leaders from any department (medical, clinical, administrative, etc. ), though in two cases it also included top managers. Research participants were recruited through a process of purposive convenience sampling except for the Mexican study when snowball sampling had to be deployed. The researchers of each study used  Flanagan's (1954)  critical incident technique (CIT) as adapted by Author 1 for his first managerial behavior study  (Hamlin, 1988)  and used subsequently for his first replication study in a British NHS Trust hospital  (Hamlin, 2002).
, 2002)  may make it even more difficult to integrate supply chains. The reality of the infrastructure in Brazil and its relations with the other peculiar Brazilian characteristics are fundamental to understanding the barriers to SCM in the country. The revised complete listing for this theoretical framework is found in Appendix 1 (Supplementary Material) and has been conducted with the support of the Atlas. TI textual analysis software. Each term or expression with an idea associated with the concept of SCM, its possible practices, tools, benefits, and barriers were registered in the tool, indexing the source article and categorizing the relationships identified and explained by each author. Based on these records, Atlas. TI was able to build "webs" that represent these relationships that are grouped into two dimensions-culture and infrastructure-as shown in Figure  1  and Figure  2.
The content analysis was supported by Atlas. TI software, a tool widely used to assist in examining textual material (Bandeira-  de-Mello, 2006). According to abductive reasoning, the study started from the deductive stage of literature review that generated 183 codes (main elements synthesized in Figures  1  and 2  and in Chart 2), which were later complemented by the inductive process of analysis of the interviews that generated 127 verbalizations. The contrast between the theoretical framework and the content analysis generated a set of theoretical propositions that finalize this study. Figure  4  presents a methodological guide that describes the abductive course beginning in reviewing the theoretical framework, advancing to the data analysis, and culminating in the conceptual model, besides also indicating that part of this process, each Appendix (Supplementary Material) supports with detail and transparency of the content analysis.
Employee selection based on psychological profiles that prefer order and structure may fail to identify the talents needed for the digitized workplace. It may be time to reconsider the applicability of past evidence to present and future issues of research and practice and to overhaul the emphasis in personnel selection if needed. In this study, we explore how an employee's character shapes their fit for the modern workplace, as indicated by their trust in their ability to utilize digital technologies and tools effectively and their ability to adapt to changing demands. More specifically, we aim to identify which dimensions of personality and vocational interests are linked to employees' digital self-efficacy and agility. We examined two large data samples, the first consisting mainly of employees from various central and western European organizations in the aerospace, food and services, and banking industries (Study 1); the second stemmed from multiple publicly traded companies listed in the French benchmark stock market index CAC 40 (Study 2).
Following these aims, our initial study collected data from a sample of 309 employees at organizations from central and western Europe that were mostly engaged in the aerospace, food and services, and banking sectors to provide a first general insight into these processes. In our second study, we examined the robustness of our findings and therefore gathered 1,025 employees, thus nearly tripling the sample of our first study. Furthermore, for this second study, we conducted our data analyses exclusively at publicly traded companies listed in the French benchmark stock index CAC 40. Our data collection process thus ensured all participants were working in well-established organizations that had successfully adapted to the changing market environment and were in the process of an ongoing digital transformation.
Methods and design In the first step, to assess the hypothesized interactions between the five factors of personality, vocational interests, and digital self-efficacy, we designed and conducted an international survey study on a diverse sample of employees from various organizations, mostly based in central and western Europe. Data acquisition was conducted by the private research company Praditus, which is recognized by the French Ministry of Research and Education. The company developed a web and mobile application to aid employees in their individual development, and participants are provided feedback on their data (see  Clark et al. , 2020; Durst et al. , 2021). For this study, we collected data via the web app.
Data analysis strategy To gain the first insight into our data, we calculated Pearson productmoment correlation coefficients for all variables in SPSS (Version 26). To test our hypotheses more thoroughly, we then proposed a path analysis, allowing us to model the pathways of the participants' personality and their vocational interests to their digital self-efficacy (Fig. 1 ). We calculated maximum likelihood estimates in SPSS AMOS (Version 26) and reported standardized coefficients for the structural equation model, as well as χ2/d. f. (sufficient fit ≤ 3; good fit ≤ 2), RMSEA (sufficient fit ≤ 0. 08, good fit ≤ 0. 05), and SRMR (sufficient fit ≤ 0. 10, good fit ≤ 0. 05) as descriptive measures of the overall model fit and the CFI (sufficient fit ≥ 0. 95, good fit ≥ 0. 97) as a measure of increased model fit compared to the independence model  (Browne and Cudeck, 1993; Hu and Bentler, 1999).
Confirmatory factor analysis To analyze whether our selected scales provide sufficient discriminant validity, we conducted confirmatory factor analyses (CFA;  Hu and Bentler, 1999)  using SPSS AMOS (Version 26). For more details on the reported measures of model fit, please refer to our data analysis strategy. Additionally, we report the Bayesian information criterion (BIC) and the consistent Akaike information criterion (CAIC) as goodness-of-fit measures to allow for a direct comparison between the alternative models  (Nylund et al. , 2007; Preacher and Merkle, 2012). For both measures, lower values indicated a better fit, and a BIC disparity of at least 10 indicated a significant difference  (Rafferty, 1995). When conducting the CFA on our proposed model of five personality dimensions, six interests, and the dependent variable of digital self-efficacy, the model provided a mostly sufficient to good fit (χ 2 (1515) = 2633.
Data analysis strategy Our data analyses followed the same pattern as reported for Study 1, with the addition of the participants' agility as a dependent variable of digital self-efficacy to the structural equation model. We further proposed direct and indirect effects between the five factors of personality and vocational interests on agility via the mediating pathway of digital self-efficacy. To obtain robust estimates of the indirect paths' significance, we employed 5000 bootstrapping samples and reported standardized total, direct, and indirect effects, including the upper and lower bounds of the 99 percentile confidence intervals for the indirect pathways. Data analyses were again conducted in SPSS (Version 26) and SPSS Amos (Version 26).
Future research should be able to overcome this issue by employing extended measures of personality, such as the  NEO-FFI (McCrae and Costa, 2010)  or BFI-2  (Soto and John, 2017b). The latter would further allow more detailed insights into the distinct impact of the 15 personality facets captured by this measure. Nevertheless, Likert-type measures share the issue of not being deception proof. However, participants had no vested interest in manipulating their personality assessment because the data were collected anonymously, thwarting the possibility of drawing inferences about individual subjects; notably, personality assessments conducted in personnel selection processes could incentivize deception. To counteract this, alternative "fake-proof" ways of measuring the Big Five have been proposed, including relative measures requiring participants to choose between statements assessing different dimensions of personality  (Hirsh & Peterson, 2007) , as well as a rapid response measure requiring quick and thus hard-to-manipulate decisions  (Meade et al.
Further conceptualizations relevant for employee selection that have been brought up in the past include narcissism and grit. However, the Big Five model was shown to fully encompass both narcissism, which constitutes the inverse of agreeableness  (Zajenkowski and Szymaniak, 2021) , and grit, which is largely engulfed by conscientiousness  (Credé et al. , 2017; Ponnock et al. , 2020; Schmidt et al. , 2018). Lastly, the method of data acquisition through a computer-based questionnaire survey presents an inherent technological hurdle that individuals who lack digital skills may not be able to overcome. Thus, participants in this study might possess an above-average tech savviness compared to the broader public. To assess a distribution of digital selfefficacy that is representative of the population, future research could conduct studies with even more accessible means of data acquisition.
‡ This research is part of the  Agriculture and Forestry research program  by the  Climate Economics Chair. The authors want to thank the  Climate Economics Chair  for financial support. The BETA contributes to the  Labex   ARBRE ANR-11-LABX-0002-01. The authors acknowledge very valuable comments from the participants of the  CEC  and TSE seminars, of the 2020 RMA annual conference in Montreal and of the 2020 EAERE congress in Manchester.
Sample and data collection The sample of this study was drawn from multiple industries, including apparel, pharmaceutical, software, and information and communication technology, in an emerging market. Bangladesh has become the world's second largest apparel exporter  (Paul, 2020) , a new IT hub in South Asia  (Ahmed, 2019) , as well as a rapidly growing pharma exporter (Biz Data Insight, 2020). As a developing economy, however, Bangladesh lacks good infrastructure and government institutions, which are important to the emergence of such successful export industries. These characteristics of the domestic environment emphasize the necessity of networking and entrepreneurially oriented behavior for internationalization-seeking firms, and, consequently, make Bangladesh a suitable context in which to investigate internationalizing firms' network-related capabilities and their boundary conditions.
We collected data in person via a structured questionnaire, copies of which were sent to a sample of 500 exporters randomly drawn from the export directories of the aforementioned industries. After eliminating missing values and conducting a normality test on the 204 completed questionnaires we had received, we were left with 198 questionnaires (a response rate of 40%). Several precautions were taken before conducting the survey to eliminate common method variance (CMV). We pretested the survey instrument and protected the identity of the respondents; to psychologically separate the independent and dependent variables, we used filtering questions  (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). The possibility of CMV was tested with Harman's onefactor test  (Podsakoff et al. , 2003)  in a principal component analysis using SPSS 24 software.
We then apply  Ostrom and Basurto's (2011)  analytical tool to scrutinize changes in rules in a real-life case study, which few empirical works have done since their paper was published in 2011  (Baur and Binder, 2013; Futemma et al. , 2015; van Karnenbeek and Janssen-Jansen, 2018; Ostrom, 2014). Our aim is to understand the institutional basis of the governance system through the linguistic statements (deontic) that compose it at each period that correspond to a different institutional configuration of the system. The grammatical syntax serves as a basis for collecting, presenting, and analyzing data to code institutional rules, in a way that gives substantive meaning to the study of change in institutions. We collected original data on the PGS from Ecovida Agroecology Network, the oldest PGS in Brazil.
Data collection Our aim was to understand the institutional basis of Ecovida PGS through the linguistic statements (deontic) that compose it at each period that characterized the different institutional configurations of the system. According to  Crawford and Ostrom (1995) , such work requires qualitative research methods, including in-depth interviews or archival retrieval. We triangulated document analysis, semistructured interviews, and participatory observations. We analyzed major documents including the Law of Organics no. 10. 831/2003, its regulation by Decree no. 6. 323/2007, and the publication of Normative Instruction 19/2009, which provides information on the functioning of the different control mechanisms, including PGS. We also checked all infra-legal rules created by Ecovida itself to orientate farmers' practices.
The secondary data were checked and compared with different actors' interpretations in semi-structured interviews carried out from September to December 2018 with two policymakers, representatives of four social movements, 14 extension technicians, and 15 PGS-certified farmers belonging to five recent and former local groups of the two oldest regional groups of Ecovida (Serra Gaúcha and Litoral Solidario). The interviews were recorded and transcribed to help us clarify and cross check findings. While the rules formally prescribed by a national government are easily identifiable, we also needed to understand the processes by which rules change at the community level. As argued by  Ostrom and Basurto (2011: 318) , 'we frequently do not know which rules are accepted by individuals in their everyday interactions.
Data To explore public perceptions, we developed a survey with 21 Likerttype items (i. e. , statements) to collect comparable data from each city. The list of items was designed to operationalise the political agenda and our own understanding of the debate on forests and the BE in Europe (Table  1 ). However, some items toward the end of the list were created to reflect certain "aspects of worldviews", namely epistemology, anthropology, and social imaginary  (de Witt et al. , 2017). As much of the debate focuses on climate science, four items dealt with carbon stocks and their link to current forest management practices and related support to forest owners. Four items measured prospects for the main political promises of the FBE, namely for reducing dependency on fossil fuels and for bringing well-being to rural areas.
Petersburg (Russia), Uppsala (Sweden), and Vienna (Austria), each of which is an important university city. We collected the data faceto-face to allow for instructing the respondents in completing the survey. For practical reasons, we resorted to convenience sampling and collected the data from crowded public spaces (i. e. , city squares, train stations, malls), prioritising local population and excluding tourists. This however meant that we chose not to ask more sensitive questions about social class, education, or political leaning. The data collection took place during 2019. In total, we received 1534 completed surveys. As the intention was not to sample rural residents, we first excluded 183 respondents for identifying themselves as such. Next, we omitted 415 respondents, majority of which from Padua, who strongly disagreed with being familiar with the FBE to guarantee that our sample comprised people who were at least roughly familiar with the term.
Acknowledgments We want to express our sincere gratitude to everybody who took part in the survey in one of the eight cities. We were able to conduct this work under the PerForm (Perceiving the forest-based sector in the bioeconomy) pan-European co-operation network supported by the  European Forest Institute (EFI). Additional funding that enabled the completion of this project was received from the  Kone Foundation  (Malkamäki,  201805496 ),  FORMASthe Swedish Research Council for Sustainable Development (Holmgren ,  942-2016-30 ),  FFGthe Austrian Research Promotion Agency  (Ranacher,  865905 ), and the  Strategic Research Council  affiliated with the  Academy of Finland  (Toppinen,  335241 ).
Acknowledgements: This work has been supported by the  French Agence Nationale de la Recherche , reference  ANR-19-CHIA-0013-01 , and grant  PID2019-111544GB-C21  funded by  MCIN/AEI/10. 13039/501100011033. The last author was supported by mobility grant  PRX21/00488  of the  Spanish Ministerio de Universidades.
Methodology The Systematic Literature Review (SLR) has been introduced in management research as a methodology for literature review to develop a scientific synthesis in response to a specific question. The SLR differs from the traditional narrative review in the sense that it adopts a transparent, scientific, and reproducible process that aims to minimize bias  (Tranfield et al. , 2003). The choice of a systematic type of literature review is due to the desire to synthesize the state-of-the-art on customer knowledge to create a solid understanding as well as foundations for future research. We conduct the searches using EBSCO. The EBSCO catalog contains 375 multidisciplinary databases and covers a wide range of academic subjects. The first query on the EBSCO search engine with "customer knowledge" resulted in 907 articles published between 2000 and 2020.