dataesr/scientific-paragraphs-categorization huggingface dataset:
Analysis technique The compiled data was analysed by theme  [15]. Once the transcription had been completed, all interviews were entered into the ATLAS. ti software (version 7. 5. 4; ATLAS. ti Scientific Software Development GmbH, Berlin). The coding and analysis was done in accordance with four of the CFIR domains and their constructs  [9]. Throughout the analysis, the perspectives of professionals and decision-makers were compared. Where agreements and differences were found, these are indicated. The analysis was carried out by two researchers. The results of the investigation were discussed in joint sessions of the research team, with any disagreement being resolved through a debate.
Both order engines are compared on the total cost performance criterion, which includes the purchase cost, the inventory cost, the shortage cost, and the multi-item cost. In the experiments, the multi-item constraint is a Franco penalty, as described in the section 2. 1, so the multi-item cost includes only eventual Franco penalties. To conduct experiments, we generated twenty different instances, each containing ten items. We assume perfect forecast, i. e. we assume that we perfectly know the demand distribution of the items. In every instance, all the demand distributions of the items are stationary Poisson distribution, and we assume all the unmet demand is lost. The parameters of the instances we used are detailed in the tables 1 and 2. The Integer Linear Program has been implemented Instance n°λ 1 λ 2 λ 3 λ 4 λ 5 λ 6 λ 7 λ 8 λ 9 λ 10 1 10 10 10 10 10 10 10 10 10 10 using the PuLP library in Python, and solved using the COIN-OR Branch and Cut (CBC) solver.
METHODS Sample We surveyed entrepreneurs (i. e. , self-employed, start-up entrepreneurs, and owner-managers of small and medium-sized businesses) in 20 countries across North and South America, Asia, Europe, and Oceania 11  from mid-April to early September 2020. Our sample includes countries that were among the worst affected (measured by deaths per capita: 12  Italy, Spain, UK, and the USA) and those with low fatalities (Australia, Japan, and New Zealand) in the first wave of the pandemic. These countries represent 73% of the world's GDP and are home to 56% of the world's population. 13 s we were collecting data during the pandemic, we recruited entrepreneurs through the distribution of an online survey via entrepreneur associations, entrepreneur networks, incubators, banks, and social media.
While most firms in our sample were created by the entrepreneurs we surveyed (84. 4%), our sample also included some family businesses and businesses that were bought and thus of older age. In all cases, the surveyed entrepreneur was owning and managing the business on a daily basis or acting as CEO. (Lucas & Donnellan, 2012). The average correlation of the single item measure with the wellestablished 5-item Satisfaction with Life Scale  (Diener et al. , 1985)  was r=0. 67, p<0. 001, N=426 across the four countries where we collected data on both (Australia, Poland, Spain, and USA; ranging from r=0. 65 for Spain to r=0. 80 in Poland). To get a sense of whether entrepreneurs' life satisfaction was negatively impacted by the pandemic, we compared the life satisfaction in our sample of entrepreneurs to existing pre-pandemic life satisfaction data of population representative samples of the self-employed (N=3,941) from the WVS.
To strengthen confidence in our measures of opportunity agility and planning agility, we explored evidence for convergent and discriminant validity. In terms of convergent validity, agility as a form of adaptive action should overlap with creativity (i. e. , the generation of useful ideas to solve problems)  (Amabile, 1988)  and with effectuation  (Sarasvathy, 2001). For discriminant validity, we would expect no correlation with causation (which is focused on planning and execution rather than flexibility adapting to changing circumstances)  (Sarasvathy, 2001). We found evidence for convergent correlations with creativity for opportunity agility and planning agility (r=0. 32, p<0. 001 and r=0. 21, p<0. 001, N=2,754; 18 countries except Germany and USA). Data on effectuation and causation comes from the Indian entrepreneurs who participated in our study.
e. , pre-pandemic, dummy coded 0 = no, 1 = yes) as a proxy for resource-availability, which has been linked to crisis-preparedness  (Williams et al. , 2017). In terms of entrepreneur characteristics, we include gender (women = 1, men = 0) and the respondent's age (in years). Education is measured as the highest level of education completed. We included two dummy variables: "secondary education," coded 1 = secondary (highschool/vocational) and 0 = less than secondary education and "university education," coded 1 = at least a bachelor's degree or equivalent and 0 = no university education. Finally, we controlled for the week of data collection (i. e. , the week in 2020 that the entrepreneurs responded to the survey) to account for dynamics related to the pandemic and government response. Data collection extended over several weeks as we wanted to make sure that entrepreneurs who were harder to reach also had a chance to respond.
Finally, we adjusted the week of data collection for the time that had passed since the beginning of the lockdown in that country (Table  A20 ), which strengthened the findings supporting H1. variables and when we treat life satisfaction as ordinal variable and estimate probit regression, the interaction between opportunity agility and planning agility (H3c) weakens to p=0. 051 instead of p<0. 05. We also conducted longitudinal analyses on a subset of our sample from Poland and Spain to test for possible reverse causality of wellbeing on agility. We used data on pre-crisis wellbeing collected in Jan/Feb 2020 and included our control variables. In line with our theoretical model, adverse impact was a stronger and significant predictor of opportunity agility and planning agility compared to pre-crisis wellbeing (Table  A21  of the online supplement).
Unlike general cross-national datasets (e. g. , World Values Survey), our data can uniquely shed light on what is entrepreneurship-specific about entrepreneur wellbeing. Our study also broadens general research on entrepreneur wellbeing, which typically does not consider country context  (Stephan, 2018; Wiklund et al. , 2019)   25  and it complements conceptual accounts of the agility of large firms across countries  (Gomes et al. , 2020; Shams et al. , 2020). We offer insight into how a newly devised formal institution (lockdown regulations introduced in response to the COVID-19 crisis) can constrain and enable entrepreneur agility and impact wellbeing. Establishing links between crisis, adversity, agility, and three types of wellbeing, in a sample of countries that represent 73% of the world's GDP and are home to 56% of the world's population contributes to the generalization of our results.
There was some variation with how the pandemic started and the types of lockdowns that were implemented across countries, which is why we collected data from April to early September and why we controlled for the precise week of data collection for each respondent in our study. Future research can examine persistence throughout the pandemic and its different stages as well as long-term outcomes post-crisis. For instance, how might entrepreneurs learn from their agility? Can early agility make them and their businesses more resilient during future crises? The two different crisis responses ("act" or "wait-and-see") could be explored in more detail and depth (e. g. , qualitatively) over different time periods. Third, we assessed the adverse impact of the pandemic on entrepreneurs' businesses through reduction in sales/trading and perceived threat to survival.
Funding and acknowledgements The Polish and UK studies and the coordination of this research project were co-funded by the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Sklodowska-Curie grant agreement No 793117 ('Positive Entrepreneurship '). The UK study was also supported by  King's Business School , the  National Enterprise Network, Westminster Business Council, Midtown Business Club, Hammersmith & Fulham Chamber of Commerce, Southwark Chamber of Commerce, Spitafields Small Business Association, Make it Ealing, Ealing Acton Business Club, StartUp Richmond, Barking  and  Dagenham Chamber of Commerce, Hertfordshire Chamber of Commerce and Newham Chamber of Commerce. In Australia the study was supported by the  Australian Research Council. In Bosnia  and Herzegovina the study was supported by the  Ministry of Education, Science and Youth of Sarajevo Canton.
In Canada the study was supported in part by funding from the  Social Sciences and Humanities Research Council. In Chile the study was supported by  CORFO  and the  Aubery Chernick Foundation. In France the study was supported and funded by the  LabEx Entreprendre (University of Montpellier and Montpellier Business School)  ( ANR-10-Labex-11-01 , funded by the  French government)  and by the public research center  Montpellier Research in Management (University of Montpellier ). We would like to thank the  Chamber of Commerce and Industry of the department of Pyrénées Orientales  which participated in setting up the French part of this survey. In Germany the study was funded by the TransCampus grant, supported by the  Federal Ministry of Education and Research (BMBF) , TransCampus is a partnership of King's  College London  and  Technische Universität Dresden.
In Japan the study was supported by  JSPS KAKENHI  Grant Number  JP 20H01530. In New Zealand the study was funded by  Waikato Management School , the  University of Waikato , and supported by the  Waikato Chamber of Commerce  and the  Sustainable Business Council. The Norwegian study was supported and funded by the  Center for Innovation Research at the University of Stavanger Business School. In Spain the study was co-funded by  Fondo Europeo de Desarrollo Regional (FEDER)  and  Junta de Andalucía's Consejería de Transformación Económica, Industria, Conocimiento y Universidades , under the operational program FEDER Andalucía 2014-2020;  Thematic Objective 01 -«Refuerzo de la investigación , el desarrollo tecnológico y la innovación» and Specific Objective 1. 2. 3. «Fomento  y generación de conocimiento frontera y de conocimiento orientado a los retos de la sociedad, desarrollo de tecnologías emergentes», through reference research project ( PY20_00856 ).
Co-financing percentage FEDER 80%. In addition, this paper is part of the Grant  PID2020-114751RB-I00 , funded by  MCIN/AEI/10. 13039/501100011033. In Sweden the study was supported by the  Swedish Research Council for Health, Working Life and Welfare (FORTE)  Grant no  2017-01063  and Grant no  2019-01311. Adversity, Agility, and Entrepreneur Wellbeing 6 Act or Wait-and-See?Adversity, Agility, and  Entrepreneur Wellbeing  across Countries during the COVID-19 Pandemic.
We plot shareholder sentiment from the early days of the colonial project involving highly speculative shareholders and swashbuckling management to subsequent periods when the investment had not met shareholder expectations. We analyse how sentiment varies over the period and against the BSAC's contemporaneous share price. We segment the data by director opening addresses, shareholder questions and director answers to shareholder questions. We use manual content analysis. Based on conversation analysis, we consider director and shareholder turn-taking and their moves during their turns. We segment shareholders' moves between sentiment and other moves and between approving shareholders and dissenting shareholders asking awkward questions or otherwise critical of the BSAC management. Our database facilitates the study of nineteenth-century GMs, one of the earliest such studies to our knowledge.
Taylor (2013, p. 684)  reports that except for  Newman (1983) , nineteenth-century company meeting reports have been little studied. He observes that Newman's short article does not seek to analyse their wider significance. We contribute to the prior literature in four ways. First, our unique verbatim GM minutes permit a depth of analysis of these meetings. Our verbatim database allows us to study director and shareholder interactions at the nineteenth and early twentieth century GMs of our case company, in the form of turns and moves. Second, our study contributes to a limited but growing stream of research on AGMs in terms of their function as fora for accountability. The BSAC is one of the earliest examples of a dual missions' company, arising from its royal charter. We contend that the BSAC's dual missions of generating shareholder returns and pursuing an imperial mission compromised accountability.
Based on the same database,  Carrington and Johed (2007)  analyse interactions at 36 Swedish AGMs to examine the extent to which they construe management as a good steward. They analyse the time devoted to agenda items and the number of questions asked, referencing four categories of issues. Catas us and  Johed (2007)  approach AGMs as a social practice involving dialogue where participants have accountability discussions and discuss accountability issues together. They assume from their analysis that shareholders are democratically invited to participate in the AGM and all shareholders have the right to be heard. How the meeting is managed may compromise these aspirations. Manipulation by directors may mean that in practice not all shareholders are heard. GMs may play out as the performativity of governance  (Pernelet and Brennan, 2022)  and the performativity of accountability  (Scott and Orlikowski, 2012).
Database We have a full set of annual reports from the BSAC's incorporation in 1889 to the end of the BSAC's administration in 1924/25. From these records, we compile a full list of AGMs and EGMs. As summarised in Table  1 , the BSAC held 38 AGMs and EGMs during that period. We obtain the GM reports from the Gell  [8]  archive at the Derbyshire Record Office in Matlock, UK. We collect an incomplete series of 29 GM reports (see Table  1 ). Some of the reports include text for both an AGM and an EGM. The discussions of the AGMs and EGMs are intertwined in the reports. It is not possible to accurately disentangle the text that relates to the AGMs and EGMs. Therefore, we analyse the text as single meetings. We amalgamate the reports of four AGM and EGMs held on the same day  (21. 4. 1898, 26. 2.
1908, 22. 2. 1912, 27. 2. 1913). This amalgamation leaves 25 sets of meeting reports for analysis (see Table  2 ). The first author photographed the reports of the GMs. We commissioned a transcription company to convert the photographs to digitise all text. We refined the total body of text (185,975 words, untabulated) by removing title pages, the publisher name, copies of letters sent to shareholders in advance of meetings (attached as appendices to reports) and the list of Company officials present at meetings. Thus, only text of words verbally spoken at the GMs remains in our refined text database (176,002 wordssee Table  2 ). The BSAC directors conducted AGMs in three parts. First, the BSAC President and other company officials delivered opening addresses to meetings. Opening addresses included a review of the period, discussion of the objects of the meeting and special presentations by directors (e.
g. following a tour of Rhodesia by directors in 1907). Second, after the addresses by company officials, shareholders were permitted to ask questions. Third, the directors then responded to these shareholder questions. We divide the total refined text from the meeting reports into these three sections for analysis. Table  2  summarises the number of words and sentences in the sections of the GM reports. Opening addresses comprise 69% of the database, with shareholder questions making up 19% and director answers 12%, respectively. We retrieve data on the BSAC's share price from Yale's International Center for Finance (n. d. ) Investors' Monthly Manual database.
Data analysis This section describes our approach to manual content analysis of our data. The level of analysis is director and shareholder turns, followed by director and shareholder moves. We differentiate two types of shareholder turns: shareholder sentiment and other shareholder turns. The BSAC meetings were a combination of political rally and corporate accountability. We choose sentiment analysis as our research method to assess crowd behaviour reflecting the sentiment of the verbal discussions between company directors and shareholders. We extract shareholder sentiment from the whole dataset. We extract director and shareholder turns from the shareholders' questions and directors' answers sections of the dataset only. Using an Excel spreadsheet, we extract all incidents of dialogue.
Shareholder sentiment according to individual turns to speak. Each time a person speaks is one turn. We inserted each turn into a spreadsheet to ensure a standardised coding approach. We collapsed the text in the coding spreadsheet. We read the full-text document on one screen and coded the turns in the spreadsheet on another screen. First, we analyse director-shareholder conversational interactions. We develop our analytical framework from an abductive process of oscillating between the data and our research design. We classify director moves into five topic categories: (1) ritual, (2) company performance/position, (3) colonial project, (4) idolisation of individuals and (5) response to shareholders, etc. We classify shareholder moves into four topic categories: (1) approving moves, (2) dissenting moves, (3) requests for information and (4) shareholder ritual.
Next, we identify expressions of shareholder reactions through sounding off recorded in the minutes by searching for the terms "Cheer(s)/Cheered", "Hear, hear", "Laughter", "Applause", "Uproar" (see Table  3 ). In subsequent analysis, we classify shareholder sentiment between positive and negative sentiment. In our entire database, shareholders express no negative sentiment during directors' speeches. Negative sentiment only arises during the question-and-answer sessions. Table  3  shows the nature of shareholder sentiment at various BSAC GMs. Table  4  reveals our approach to the analysis/coding, based on two exchanges during the 1895 EGM. The two exchanges involved 14 turns, three shareholder sentiment incidents, six by directors and five by shareholders. The first exchange comprising three turns involves a dissenting shareholder raising issues.
BSAC general meetings as theatre (RQ2) This section considers shareholder sentiment over the study period and compares it with the BSAC's share price. Given how poorly the share price performed and the lack of dividends, a key agenda for the directors at the BSAC GMs was to maintain shareholder hope, in which theatre had a role to play. 5. 2. 1 Shareholder sentiment turns (RQ2a). Meeting minutes record shareholder reactions during the meetings. Figure  1  earlier summarises the frequency of cheers, "hear, hear"s, laughter and applause in graphical format. Our database contains 634 cheers, 545 "hear, hear"s, 201 instances of laughter and 71 applauses. The minutes note the intensity of shareholder reactions, in terms of "loud" (cheers, laughter, applause). The minutes record one bout of cheering as "loud and prolonged", reflecting the period of greatest shareholder zeal for the BSAC.
Future research We have a unique database of verbatim GM meeting minutes. We intend to develop a deeper analysis of the interactions between directors and shareholders during their turns and moves, especially the interactions between the directors and the approving/dissenting shareholders. Because of the zeal and evangelism for the greater colonial project of building the British Empire, our dataset is strongly theatrical on which our future research will focus. Such detailed records of company GMs are available nowadays because, increasingly, GMs are recorded. This permits researchers to analyse the words spoken at GMs and also their choreography, performance and body language. Text mining software is now capable of interrogating such large amounts of data. While much GM activity is ritual, some topics (e.
The first click and drive store was set up in 2000 in France, and click and drive stores have flourished throughout this country in the last decade. 3,219 click and drive stores were identified in 2017 in the TradeDimensions database. This paper aims to assess the impact of e-commerce on retail competition and consumer welfare. Some papers like  Bonnet and Etcheverry (2022)  and  Duch-Brown et al. (2017)  examine the effect of e-commerce in specific markets. However, using home-scan data on soft drink purchases in France, I developed a model of store choice to better understand consumer preferences, not for a specific brand but for a store. Thus, I can study the effect of the online distribution channel in the grocery market and not in one market in particular, like soft drinks or pasta. This paper is the first paper that assesses the impact of e-commerce using a store choice model.
Store choice has been estimated in the literature using different methods. Dubois and Jodar-Rosell (2010)  and  Smith (2004 ) model consumer's store choice using a discrete-continuous choice model and estimate the sensitivity of store choice to an overall index of prices for each store. I develop a discrete store choice model. Bell et al. (1998) ,  Briesch et al. (2009)  estimate offline store decisions and  Melis et al. (2015)  estimate online store choice. Chintagunta et al. (2012)  constructs homogeneous channel choice probit models using a panel dataset of households that shop at a grocery retailer in Spain. They estimate the transaction costs for online and offline shopping trips with monetary measures. Wieland (2021)  studies the elements that drive online and offline store choice using a nested logit model using a consumer survey conducted in Germany that focuses on groceries, electronics, and furniture.
Data I use a dataset of grocery purchases in 2017 collected by the society Kantar. A French representative household panel makes those purchases. I use the 18 first weeks of 2017 as the initialization period for the loyalty variable, so I keep only households that buy in the 18 first weeks of 2017 and the 34 last weeks of 2017. I observe 1,486,137 grocery shopping trips. A shopping trip is indexed by the subscript (c,r,h,g) for distribution channel c, retailer r, household h, and day g. A store s corresponds to a distribution channel c and a retailer r 1. 1. 93 grocery shopping trips per week with a standard deviation of 0. 88. There are two main types of e-commerce in the food industry: orders with deliveries and click and drive, where consumers buy online and then pick up the order by car.
Major retailers have opened an online distribution channel. There are two types of click and drive stores: the "solo" click and drive with an autonomous and remote warehouse and the "attached" click and drive with a dedicated warehouse but attached to a classic store or with a shared warehouse with a brick-and-mortar store  (Colla and Lapoule 2012). In the Kantar TNS Worldpanel dataset, we do not know the type of click and drive store where households purchase groceries. We only know the type of click and drive stores that have mainly been opened by each retailer, thanks to the TradeDimension dataset. Table  6  in the Appendix shows the kind of click and drive stores chosen by the leading retailers. Retail groups do not have the same strategy. Retailers 2 and 6 mostly built solo click and drive stores, and retailers 3, 4, 5, and 8 mainly built attached click and drive stores.