dataesr/scientific-paragraphs-categorization huggingface dataset:
Individual level As compared to other IB studies, family firm-centric studies tend to place greater focus on behavioral aspects. However, most family firm internationalization studies take for granted individual behavioral aspects that shape decision-making, such as family-centric, affect-based, and/or emotional factors. Indeed, quantitative studies using archival data often assume but rarely measure behavioral characteristics like stewardship, altruism, and risk or loss aversion. Tsang (2006: 999 ) labels this practice ''assumption-omitted testing'' and argues that such treatment of behavioral assumptions leads to unconvincing and contradictory empirical results in theory-testing studies. For example, multiple authors report that family involvement in ownership and/or management lessens internationalization due to the family's desire to avoid SEW dissipation  (Banno& Trento, 2016; Dou et al.
Exporters can also use retention quota of their repatriated export income for setting up offices in foreign countries to facilitate marketing and input sourcing activities  (Kazemi, 2015). RMG and garment accessories firms receive assistance in manufacturing and marketing in the form of seminars and workshops from public agencies. Further, the Export Promotion Bureau (EPB) works as a key agent to develop and promote the export sectors. The Trade Information Center (TIC), one of the information divisions of the EPB, maintains an extensive library to house recent trade directory, statistical data, and market survey of different countries, as well as publication from the WTO, World Bank and other trade-related institutes  (EPB, 2020). The TIC facilities locating potential buyers by using international database, which helps the exporters overcome their uncertainties regarding exporting to a particular country.
Sample and data collection Primary data were collected from a sample of exporting firms in the RMG industry of Bangladesh. The industry is an ideal context for IB research, especially for investigating the impact of institutional support for the following reasons: Bangladesh is the third largest apparel exporter in the world (Statista, 2019), with its RMG sectors generating more than 80% of the total export earnings  (Khan, 2021) ; the government of Bangladesh has offered a large number of policy initiatives and support schemes that help the industry flourish  (Ahmed and Brennan, 2019b). Firms in the industry are born exporters as required by the law to avail of the assistance provided by the government  (Faroque et al. , 2021a). Past research focusing on the internationalization and export performance of apparel firms in Bangladesh has predominantly selected sample firms from two associations, the BGMEA and the BKMEA (e.
g. ,  Ahmed and Brennan, 2019a; Ahmed and Brennan, 2019b; Faroque et al. , 2021a, etc. ). This study, too, draw the sample from these associations' directories. From over 4,000 apparel exporting firms listed as the members of the BGMEA and the BKMEA, every third firm in the list was randomly selected, which resulted in 1,000 sample firms. 718 completed questionnaires yielded a response rate of approximately 72%. Lastly, questionnaires with missing values were dropped resulting in 705 valid questionnaires. This research used several techniques to maximize the response rate  (Forza, 2002). First, a forwarding letter from the management of the BGMEA and the BKMEA with a request to cooperate with the researchers was obtained. Face-to-face survey method was administered to increase data validity  (Yamakawa et al.
, 2013). Given the large scale of the survey, a research team familiar with such a research method and having prior experience in collecting data from the apparel industry of Bangladesh, was employed  (Faroque, 2015). The data collection process was supervised by the lead author of the study. The other authors called a small number of respondents randomly every week to confirm that the research assistants had visited them and collected data properly. Data collection took place over five months, whereas each survey lasted for twenty minutes on average. The structured questionnaire for the survey was developed following previous export promotion and internationalization research. The content and face validity of the items was assessed by two academic researchers in the field. The questionnaire was revised to address their comments.
Conclusion, limitations and future research Drawing insights from the IBV, the RBV and the RO perspective, this study analyzed how government and nongovernment sources of formal institutional support, individually and jointly, affect EIFs' export performance. It also examined the influence of institutional support on EIFs' performance with moderation of firm age and size. We collected primary data from 705 apparel exporting firms in Bangladesh and incorporated hierarchical regression as the primary method of analysis. According to the findings, the credit for firms' superior export performance should go to nongovernment institutions as well as to government ones. The findings also demonstrated that firms' size positively moderates the individual government and nongovernment assistance-performance relationships, while firm age positively moderates the resource-bundling effect.
We argue that the findings may have implications for other transition economies (e. g. , Vietnam) as they share this unique banking composition, i. e. , large state-owned banks with nationwide branch networks and small local banks which are restricted to operating locally. The rest of this paper is organized as follows. Section 2 explains the theoretical reasoning used to formulate testable hypotheses. Section 3 presents datasets, variables and empirical models. Section 4 discusses the main results. Section 5 makes conclusions and clarifies the contributions of this study.
Data As our focus is SME financing constraints, we collect sample data from the over-the-counter (OTC) market in China. 1 The OTC market is an equity trading market which provides financing for companies that have not met the public listing requirements for the Main Board Market, either because their financial disclosure standards are lower, or their trading volumes are smaller. It has thus become a vital financing venue for numerous privately-owned SMEs, such as entrepreneurial and high-tech companies, because they face challenges in obtaining loans from banks and consequently increasing barriers. A firm dataset is constructed using the China Stock Market & Accounting Research (CSMAR, http://cn. gtadata. com/) database containing general and financial information based on standardized financial statements and records for listed companies, including the firms in the OTC market.
2 We collect sample data from CSMAR, provincial bank data from Regional Financial Operation Reports published by the People's Bank of China, provincial digital financial inclusion data from Peking University Digital Inclusive Finance Index published by the Digital Finance Research Center of Peking University  (Guo et al. 2020) , and province-level data on macroeconomic items from the China Statistical Yearbook issued by the National Bureau of Statistics of China. 3  The initial sample includes all firms in the OTC market over the period 2007-2017. 4 After excluding those firm-year observations with missing values, financial firms and firms located in the province of Tibet due to its abnormal macroeconomic information, the final sample consists of 11,610 firm-year observations.
The survey's wave nature allows for finding the exact year of each country survey and matching and filling the most recent issue-level Sukuk data to each survey year for which the trust score is available. This approach is valid because trust scores remain stable across time  (Bjørnskov, 2010; Cline and Williamson, 2016). Further, we use Thomson Reuters' World EIKON database to retrieve the global sample of Sukuk issuances spanning 2001 to 2019 and collect variables related to Sukuk features and issuer characteristics. Moreover, we employ the World Bank Database to retrieve finance development and governance indicators. Finally, we use the comprehensive GLOBE culture dimensions following  House et al. (2004). In retrieving Sukuk, we apply no filters on elements   Table  1  presents the Sukuk sample decomposition by country (Panel A) and year (Panel B).
Endogeneity concerns Next, to simultaneously address endogeneity concerns, reverse causality, and omitted variables issues inherent to using OLS regression models, we employ 2SLS with IV approach. We use Quality of Institutions as the instrument variable to estimate societal trust in the first stage and regress instrumented trust on the amount of Sukuk issued in the second stage. Quality of Institutions is a timevarying index measuring country institutional quality, with high (low) scores indicating countries with higher (lower) institutional quality. This composite measure is a weighted average of six broad governance dimensions from the WGI database, including voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of.
H7 Age and gender moderate the effects of performance expectancy, effort expectancy, social influence, and facilitating conditions on consumers' behavioral intention. Data Collection and Sample Description Data are collected through an anonymous online survey developed and operated via the web platform Qualtrics. The main focus of the survey is to collect data on the IoT users' behavioral intention in eHealth. The survey looks to measure the main determinants of users' behavioral intention toward IoT in eHealth. These determinants are IoT users' performance expectancy, effort expectancy, financial cost of the connected object, users' perceived risk, social influence for adopting IoT, and facilitating conditions toward the adoption of IoT. The references and properties of the measure scales are discussed in Section 5.
Empirical Results Analysis In this study, a partial least square structural equation modeling (PLS-SEM) approach using xlstat-PLSPM software is used to test the research model and the related hypotheses. As supported by  Hair et al. (2014) , the partial least square approach is consistent for exploratory studies and a small sample size, because it does not require normal distribution of the In addition, as recommended by  Kwong and Wong (2013)  and applied by  Karahoca et al. (2018) , the bootstrapping procedure is used to test the significance of the inner (measurement) and the outer (structural) model. This procedure calculates a bootstrap standard error and generates approximate t-values for significance testing of the structural path  (Kwong and Wong, 2013).
This paper examines the impact of renegotiations on contract renewals. Using an original dataset of procurement contracts in the French car park sector, we show that there exists an optimal level of renegotiations that positively affects the probability of renewing a contract with the same partner. This result holds only when public authorities have discretionary power during the awarding procedure. Such findings suggest that what is usually interpreted as a sign of weakness -frequent renegotiations -might well be good news that indicates that the contracting parties can make contracts adaptable over time.
If renegotiations result in a significantly negative outcome, parties are not prone to contract again. To this end, we use an original database of 252 public contracts in the French car park sector, and we examine the impact of different dimensions of contractual renegotiations on the probability of renewing the contract with the same partner. Our results suggest that there exists an optimal frequency of renegotiations, in which renegotiating per se should not be interpreted as a sign of failure of the relationship. In addition, we find that while some renegotiations clearly increase the probability of renewing a contract, others do not. This suggests a positive, negative or neutral influence on contractual surplus -depending on the frequency and type of renegotiations. The remainder of this paper is organized as follows: In the next section we review the related literature and develop hypotheses.
Types of Procurement Contracts Our dataset of car park contracts is characterized by the existence of two different types of contracts that mainly differ along the duration and the discretion that is given to the public authority during the tendering process: Concession contracts and Service contracts. Concession contracts are long-term contracts in which private operators build or deeply renovate the infrastructure, deliver the service, and keep the fees that are paid by users. Consequently, Concession contracts are subject to political, economic, social and technical changes that may occur during their execution. Such changes may be exogenous to the contract (technological developments, economic shocks, changes in legislation or legal interpretation), or the changes may directly result from internal drivers (evolving business requirements) or contract maladaptations (inappropriate initial contractual design).
Data In the French car parking sector, data are neither centralized nor collated because of the lack of a national regulatory authority. Therefore, in order to generate the dataset that we use in this study, we examined all of the expired contracts that were signed between one of the biggest operator and 136 different public authorities over a  42-year period: 1965-2007. To explore whether the sequence of renegotiations influenced contract renewals, we considered a contract to have been renegotiated when a revision occured that was not envisioned in the original contract. In the end, we examined 252 expired contracts and their respective 782 renegotiations.
Dependent Variable Our dependent variable -Renewed i -takes the value of 1 if the expired contract was renewed with the same private partner at the contract renewal time and 0 otherwise. The renewal rates that are in our dataset were 45% and 78% for Concession and Service contracts, respectively (summary statistics are provided in Table  1 ). In practice, there are several possible reasons why a contract is not renewed: (i) the public authority selects another operator; (ii) the public authority returns the activity to public provision; or (iii) the private operator chooses not to rebid for the contract. While a general explanation is that the parties are unwilling to contract again because of dissatisfaction in their previous relationship: the information that we collected from our interviews with the head of the legal department of the car park company confirms that in practice the incumbent private operator is always a candidate for its own succession.
Renegotiation Variables The first way to characterize renegotiations is to distinguish between contracts that have been renegotiated and those that have not. Accordingly, we use a dummy variable -No_Reneg i -that takes the value of 1 if the contract i was not renegotiated at all during its run and 0 otherwise. In our dataset, more than 73% of Concession contracts were renegotiated compared to only 33% in the Service sample. This difference is because Service contracts generally involve simpler unbundled tasks that give rise to shorter contract durations than with Concession contracts. This observation is in line with the findings of  Guasch et al. (2008) , who pointed out that contract uncertainty explains the probability of renegotiation. However, examining the occurrence of renegotiations is a crude measure because it ignores information on the frequency and types of renegotiations.
Conclusion Using an original dataset of 252 expired contracts in the French car parking sector, we examined how renegotiations influence the continuation of contractual relationships. We estimate the effect of the frequency and type of renegotiations on the probability of contract renewals. The econometric results provide evidence that there exist -for each specific contract and relationship -an optimal level of renegotiations. Our paper provides new insights into the issue of renegotiations, which have generally previously been analyzed through the lens of opportunism. We provide evidence that, on the one hand, a high frequency of renegotiations may indeed lead to higher transaction costs (and to potential opportunism) and thus negatively influence contract renewal. But, on the other hand, if renegotiations are aimed at adapting contractual terms to their environments and thereby increasing efficiency, the net effect could be positive.
Employee welfare index We measure employee welfare through the Kinder, Lydenberg, Domini Research & Analytics (KLD) database, which measures firms' CSR attributes based on seven dimensions: community, diversity, employee relations, environment, product, human rights and corporate governance, for various indices (e. g. S&P500 Index, Domino Index (DS 400), as well as 3000 largest public companies by market capitalization). Following previous studies (e. g. Ghaly, Dang and Stathopoulos, 2015; Landier, Nair and Wulf, 2009; Verwijmeren and Derwall, 2010) , we also exploit employee relations data from the KLD database as a proxy for employee welfare, because the use of this database to measure employee welfare has several advantages. For example, this database uses multiple pre-specified criteria to measure each dimension, allowing various aspects of that dimension to be covered.
Sodeman (1995)  mentions that it is far more specific than the Fortune rankings, with an enriched measurement along with a number of widely used social-investment criteria. Further, this database's coverage is comprehensive and includes multiple stakeholders and annualized longitudinal assessments  (Ruf, Muralidhar and Paul, 1998). Due to its relative advantages, academic research widely uses this database to examine a firm's relations with its employees  (Bae, Kang and Wang, 2011). The employee relations dimension of KLD assigns a strength score to each firm annually based on parameters of union relations, employee involvement policies, retirement benefit strengths, profitsharing programmes, health and safety standards and other strengths. The weakness score dimensions include union relations, workforce reduction, health and safety standards, retirement benefit concerns and other weaknesses.
The details of each parameter are defined in Appendix A. We use all US firms in the KLD stats database over 1996-2017 as our initial sample. After merging this data with Compustat using the global company key (GVKEY), we obtain the final sample of 11,451 firm-year observations. The most widely used proxy for employee relations is the net score obtained by summing the strengths score and subtracting the aggregate concerns score to arrive at the net score for each year. Ghaly, Dang and Stathopoulos (2015)  and  Verwijmeren and Derwall (2010)  used this measure as a proxy for employee well-being in their studies, as follows: Emp_wel f are i,t = Strength i,t - Weakness i,t (1) where Emp_wel f are i,t = employee welfare score for firm i in year t; Strength i,t = sum of strengths for firm i in year t; Weakness i,t = sum of weaknesses/concerns for firm i in year t.
7 We create a dummy variable that is equal to 1 for all these states, and 0 otherwise. The third law that we use to devise our state welfare index is the Occupational Safety and Health Act (OSHA) of 1970. This law was created to ensure safe and healthy working conditions by encouraging and assisting states in their efforts towards this cause. Similar to the above two acts, states differ in the implementation of this law. We collect data for states that have their own unique approved OSHA plans from the U. S. Department of Labor and create a dummy variable equal to 1 for all such states, and 0 otherwise. 8 o create a state-level welfare index, we sum all the dummy variables on a state basis to create an index, based on scores in each set of laws. Further, to make this variable an industry-level instrument, we take the average peer state welfare score of all the TNIC-based peers outside the state in which the firm is headquartered.
ACKNOWLEDGEMENTS We acknowledge the support of the following organisations and their members, who have contributed to this review: the  Global Initiative for Asthma , the  Global Initiative for COPD , the  Global Asthma Network, The Union , the  Pan African Thoracic Society , the  British Thoracic Society Global Health Group , the  European Respiratory Society , the  Asian Pacific Society of Respirology  and the  Asociacion Latinoamericana de Torax , and the  World Health Organisation. We thank the  NIHR Global Health Research Unit on Lung Health  and  TB in Africa at LSTM (IMPALA)  ( 16/136/35 ) for facilitating this collaboration. IMPALA was funded by the  National Institute for Health Research (NIHR ) using UK aid from the  UK Government  to support global health research. The views expressed in this publication are those of the authors and not necessarily those of the  NIHR , the  UK Department of Health and Social Care , or other affiliated organisations.
Goal: The supply chain sustainability (SCS) literature is missing studies that specifically analyse factors that impact sustainability performance in supply chains, according to specific theoretical backgrounds. Within this context, this paper aims to understand how and why social capital theory (SCT) can inspire SCS studies and practice. In doing so, two research questions are addressed: (1) How has the SCS literature evolved in its application of the social capital theory?, and (2) What are the main sustainability performance factors studied in SCS?. Design / Methodology / Approach: A systematic literature review was developed. Data were collected from 12 years (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019) in two databases (i. e. EBSCO and Web of Science) and a total of 56 articles were selected and analysed through deductive and inductive content analysis.
It is important to highlight that we use the literature review as a way to build theory on SCS, i. e. we are not limited to the review outcomes but provide further analysis  (Seuring et al. , 2020)  To begin the study, we reviewed the literature in order to identify the main research gaps and to select the research question(s) (Step 1). In sequence, Step 2 involves selecting the bibliographic or article databases. For this paper, we used two main databases: EBSCO (including Academic Search Premier and Business Source Elite) and Web of Science. In Step 3 we defined the research terms, and in Step 4 we applied practical screening criteria (explained in more detail in subsequent sections). We did not complete Step 5 because we did not have restrictions concerning the methodological screening criteria.
Rigour of the research process Motivated to demonstrate rigour during our research process (Step 7), we used several strategies to ensure the reliability of our research  (Burgess et al. , 2006). First, following  Seuring and Gold's (2012)  recommendation, in order to ensure transparency and replicability of the research design, we carefully documented the entire process. In addition, similar to what other researchers have done (e. g. Touboulic and Walker, 2015b) , we carried out several rounds of analysis via the double-check approach  (Seuring and Gold, 2012)  to reduce bias during the deductive and inductive phase. Validity was established by comparing the results with an internal analysis of the database, which ensured that we were analysing the correct data.