dataesr/scientific-paragraphs-categorization huggingface dataset:
The focus on Mexico is based on the current lack of empirical studies looking at the impact of internal and external factors on the adoption of CE in emergent economies  (Chiappetta Jabbour et al. , 2020). Mexico is a developing economy with a large number of SMEs  (INEGI, 2016)  which have a significant environmental impact  (Araya, 2003). For this reason there is an intention to implement CE principles in the country  (Diéguez-Santana et al. , 2021). Empirical analysis is undertaken using structural equation modeling (SEM) implemented in AMOS software. A dataset of 165 responses from Mexican SMEs to test hypotheses obtained from the model. The results are discussed to: contribute theoretically to the understanding of the relationship between CE and SOI, examine the nature of the relationship between external factors and the integration of CE, and analyze the role of SOI to enhance sustainable performance in SMEs, combining the perspectives of institutional-based view (IBV)industrybased view and resource-based view (RBV).
Effect of digital platforms and CE on SOI Waste reduction and technology implementation (digital platforms providing analytical and processing capability to support decisionmaking) are components of SOI  (Adams et al. , 2016). There are different factors contributing to SOI. This research examines the influence of CE and digital platforms on SOI and Table  2  summarizes some of the articles looking into these relationships. Digital platforms are an aggregation of several technologies such as database, cloud computing, big data analytics, visual computing (dashboards) and computational algorithms. These platforms can enable companies to modify their processes to become more flexible and reconfigurable  (Wang et al. , 2016)  to achieve sustainable business performance  (Gunasekaran et al. , 2017; Gupta and George, 2016) , and to reduce risk  (Rodríguez-Espíndola et al.
This approach was useful because of the need to pre-establish relationships with SMEs assuring trustworthiness in order to successfully obtain information or data from them because of security concerns in the country. The sampling criterion involved SMEs operating in the Celaya region. Celaya is located in the southeast quadrant of the state of Guanajuato with a population of 681,000 people in 2020  (Macrotrends, 2020). The combination of a very economically active region, the significant investment in the area, a strategic location, and prosperous large organizations has allowed for the growth of SMEs in the area  (Ruth Del Castillo et al. , 2019). The sample of respondents included owners, managers and directors with decision-making power and first-hand knowledge regarding the operations of the company.
The data was  collected from December 2018 to October 2019. The descriptive statistics of the sample can be seen in Table  4. The sample size was decided according to the nature of data analysis to obtain robust and reliable results. Different thresholds and rules of thumb have been proposed to determine an adequate sample size for SEM. Although some traditional sources suggest including ten times as many participants as variables  (Nunnally, 1978) , more recent articles suggest a minimum of 100 and 200 responses  (Boomsma, 1985)  with at least 100 respondents  (Bollen and Noble, 2011). This indicates that a sample size of 165 responses is adequate. In fact, recent studies based on a Monte Carlo simulation analysis re-evaluate the standard rules of thumb for sample size selection with suggestions below these thresholds  (Sideridis et al.
Examining the validity of constructs utilized for SEM analysis In order to determine the reliability and validity of the latent constructs, these were tested using the Cronbach's alpha, correlation coefficient and exploratory factor analysis (EFA). Analyses were conducted using the Statistical Package for the Social Sciences software. Results to test convergent validity are shown in Table  5 , namely Cronbach's alpha, correlation coefficient and percentage of variance obtained by running EFA. Values of Cronbach's α for most latent constructs are adequate  (Bryman and Cramer, 2011; Hair, 2003; van Griethuijsen et al. , 2015) , whereas all correlations of observed items for the latent constructs are statistically significant (p-value<0. 01). Percentage of variance of the observed items explained by the latent constructs is adequate, ensuring the validity of the performed analysis (percentages are above 50%, except for SOI being at the borderline).
Purely instrumental arguments that the primary purpose of treating stakeholders well is to make more money are not particularly valuable to business ethics scholarship. The same ideas apply to corporate social responsibility (CSR). A paper that demonstrates how much money a firm can make if it is a responsible corporate citizen (perhaps with a few moderators thrown into the models) is only going to be attractive if it also explores the ethical ramifications of whatever definition of CSR the author is using. This also means that it is vitally important to clearly define the CSR construct and then, if it is an empirical paper, make sure that whatever measures of CSR are used are consistent with that definition. There are far too many papers in the literature already that make use of a comprehensive measure of CSR that is based on a measure created from data provided by a firm that gathers the data for investors and not for business ethics researchers.
In many cases, the construct validity of one of these CSR measures has not been established in the academic research literature. Also, many of these measures are based on hundreds of variables that are processed by the data providers in what amounts to a "black box," and researchers have to assume that the methods used by the data collection firm are valid. In papers submitted to the section, examples of moral as well as potentially immoral strategies and actions are welcome. Consequently, also of interest is research on the way corruption, greed, deceit, coercion, and the desire for power influence firm strategies, outcomes, and stakeholder responses. In the next section I will highlight some of the papers that have been published in the journal that fit nicely within the strategy and ethics domain.
Measurement is a big problem, at least in the CSR and stakeholder areas. For example,  Choi and Wang (2009)  measured stakeholder relations by drawing data from what is called the KLD database, using variables for employee relations, diversity, community relations, the environment, and product dimensions. Then Wang and Choi (2013) used these exact same variables from the same database to measure corporate social performance. This is not a criticism of the authors, but rather an example of a huge problem in the field-both of these papers passed through a rigorous review process at a top management journal. Moving forward, we need to make sure that, once we have clearly defined our constructs, we also make sure that there is consistency between the construct and the way it is measured. This principle applies not only to the CSR subject area, but to other topics in business ethics.
2. Beyond the big commercial databases whose primary source of income is investors, there is very little publicly available data that researchers can use to examine the value firms create or destroy for stakeholders (e. g. , stakeholder welfare). Given that so many of the interesting topics in strategy and ethics pertain to this type of welfare, creation of new databases or even a consistent set of data collection tools would be very beneficial in advancing knowledge in the field. 3. The most common dependent variable in empirical studies in strategic management is financial return in the form of profit, shareholder returns or something similar. While profits are important to the ability of a firm to achieve its objectives, including the creation of value for stakeholders, there are infinite possibilities for new studies in this section if researchers spend more of their efforts examining other dependent variables.
CSR is sometimes used as a dependent variable, and this is a good step (as long as the construct definition and measures are consist-ent). Other dependent variables could include community welfare, employee welfare, supplier welfare or customer welfare, just for a start. Some of the big databases that are already in use contain data that may be useful in creating these types of measures. Qualitative methodologies and methods can also be very helpful. The key is to think about the stakeholder and societal value that is created or destroyed as firms implement their strategies  (Harrison & Wicks, 2021). 4. Finally, new theory is sorely needed. Among the most used theories at the intersection of strategy and ethics are stakeholder theory, agency theory, stewardship theory, or salience theory. Scholars also borrow theory from other disciplines to support their arguments, which is good, but where are the new theories that are specific to strategy and ethics? In summary, the intersection of strategy and ethics offers many opportunities to address some of the problems associated with global changes and challenges.
A Stylized Framework These seven dimensions, harm, dependence, facilitation, appropriation, deception, predation and exploitation, may act in overlapping ways to support a business model with an unethical core. Such a simple framework would allow researchers to map the dependence of any given business model on each of these dimensions, perhaps with results as shown graphically as in Fig. 1 , below, for four stylized, proforma business models labeled A to D. This initial framework requires refinement in three key ways, and research is invited to explore correlations and redundancies, to add missing elements and dimensions, and, critically, to devise a means of scoring, perhaps based on large datasets.
, 2017; Urbinati et al. , 2017; Merli et al. , 2018). Individual users or consumers in the CE play a critical role by changing their behaviour towards materials re-consumption  (He et al. , 2021). Scholars agree that emerging technologies like blockchain can play an essential role in implementing CE  (Sekhri, 2018; Koscina et al. , 2019; Kouhizadeh et al. , 2019; Upadhyay et al. , 2021; B€ ockel et al. , 2021). Blockchains represent "tamper-evident and tamper-resistant digital ledgers implemented in a distributed fashion (i. e. , without a central repository) and usually without a central authority"  (Yaga et al. , 2019: 1). The database design as a distributed ledger creates a trusted network without a high-performance infrastructure in secured data centers. Blockchains can be used for registering, confirming, and transferring contracts and properties  (Romano and Schmid, 2017) , and their security, openness, and multilateral governability provide a promising technological base to implement CE business models in real life  (Kouhizadeh et al.
Data analysis We first extracted the scenario descriptions from the exam reports. We excluded 34 of the 91 scenarios in our dataset: 16 described blockchain use in environments that were not clearly CEs, and 18 were incomplete. This left us with 57 scenarios and a dataset of 40 text pages. We followed the typology building approach proposed by  Doty and Glick (1994)  to arrive at scenario clusters that represent conceptually derived and interrelated sets of ideal types. Two researchers coded the text body using qualitative content analysis  (Miles et al. , 2014). The analysis was designed as a sequence of iterative circles. In each circle, the researchers first coded the text separately and then developed a common interpretation by comparing and refining the initial categories. Involving multiple interpreters allows ensuring credibility of the data analysis by clarifying the researchers' frames of references and reducing the influence of individual recognition patterns  (Lincoln and Guba, 1985; Flick, 2014).
Sustainability management The 23 scenarios of the sustainability cluster are all based on the assumption that in the future, most aspects of consumption need to be organized in a sustainable way to save the planet. The scenario comprises three sub-clusters: In the eleven scenarios that belong to the sub-cluster product life cycle tracking, individual and organizational actors are contributing to circular recycling processes implemented by the government. Governmental actors define positive and negative sanctions to incite the recycling of products. All products are registered in a blockchain-based database with a tracing barcode. The blockchain also stores information about the product's sustainability, such as the supply chain, the working environment in the production companies, the resources used for production, or the product recyclability.
In the 7 scenarios that belong to the waste management sub-cluster, again, the government is the main actor. It uses blockchain databases for two purposes: First, to register and detect products that need to be transformed to prevent waste -such as food with close expiry dates (scenario 12) or waste that can be transformed into valuable assets such as bracelets (scenario 15). Second, blockchain databases register and monitor material that needs to be replaced in society, such as non-recyclable material or meat-based food. The blockchain also automatically assigns financial benefits to actors who contribute to replacement or transformation processes or to notifying stakeholders of product expiration dates in stores and organizing their redistribution (e. g. , for social welfare). Negative sanctions are unnecessary, as individuals and organizations actors are imprinted to reduce waste and reuse anything possible.
Acknowledgement We sincerely thank all students who participated in the course " Technological Megatrends and Innovation " in the Spring semester 2020 and donated their FTS workshop scenarios to this research. Moreover, we are grateful to the editors and reviewers of Cleaner and  Responsible Consumption  for the continuous encouragement and the constructive feedback. Bjørn S. Cience  provided us with invaluable support while working on this paper.
Scenario definitions A linear scenario was modeled to depict a completely linear flow of materials assuming that no CE strategies are adopted. It was used as a reference scenario to create a baseline for comparison and to demonstrate how much the other scenarios increase circularity or reduce environmental impact. Three scenarios were modeled based on typical approaches to accomplish circularity as defined in this study. For this purpose, the circularity framework presented by  Bocken et al. (2016)  was used and the three scenarios depict one closing, one slowing, and one narrowing strategy. An additional scenario was included to depict the combination of all three looping strategies. This choice of scenario setup covers a wide range of CE strategies that realistically can be implemented to improve material efficiency in a lawn mowing value chain and is suitable for generating sufficient data to assess the usefulness of the C-metrics.
Choice of circularity metrics A crucial criterion for answering the aim of the study was the capability of C-metrics to evaluate CE strategies that narrow, slow, and close material loops throughout all steps of a value chain. As the aim of the study is to assess material-focused C-metrics, no C-metric integrating energy use was included. In addition, no C-metric including energyrelated aspects that can capture the benefits of the chosen CE strategies was found in the literature. Four C-metrics that match the criteria and depict a methodological spread were chosen: two material flowbased C-metrics using numerical input-based data and two questionnaire-based C-metrics using a mix of numerical and nonnumerical data. These metrics were also chosen due to practical reasons: They are all made accessible through integration in computational tools.
Life cycle assessment setup In this study, SimaPro version 9. 1. 1. 7 was used for the LCA modeling, which is a sophisticated software system commonly used for this purpose  (Curran, 2015). Data related to production, transport, and waste treatment were taken from the Ecoinvent version 3. 5 database, as it contains all necessary raw material and energy processes for this study. To incorporate a wide variety of environmental impact categories, three midpoint categories were modeled: Global Warming Potential (GWP), Mineral Resource Scarcity (MRS), and Human Non-Carcinogenic Toxicity (HNCT), where GWP, in turn, affects biodiversity, MRS resource depletion and HNCT human health  (European Commission, 2010). The choice of MRS is further motivated by the fact that the chosen C-metrics intend to assess material efficiency.
Production and retail The material and energy use assumptions for the manufacturing processes were mainly taken from an existing LCA of a European gasdriven lawn mower  (Lan and Liu, 2010)  and the Ecoinvent database. Lan and Liu (2010)  model a lawn mower that is heavier than typical lawn mowers, 35 kg in contrast to 30 kg  (Saidani and Kim, 2021). To model a smaller lawn mower, a linear regression was made to calculate each material's weight in a 30-kg lawn mower. In Table  A1 , the bill of materials for the lawn mower, including 5 kg of cardboard for packaging, is presented. The same bill of materials and production data were used in all scenarios except the quality and combined scenarios, where unalloyed steel was used instead of steel alloy. In processes not related to the recycling process, cut-off by allocation was used.
Fig. 3  illustrates the manufacturing processes for the included components from raw material extraction to assembly. In the LCA setup, raw material processing was included in all the material datasets used in the component production. In regards to production location, the materials of the lawn mower are divided into two categories: metals and plastics. To reflect a typical European scenario, metals were assumed to be extracted in Sweden, which has rich access to iron ore, while plastics are manufactured in Poland, which has suitable plastics manufacturing potential. The materials were assumed to be shipped by truck, 1000 km from Sweden to Germany and 500 km from Poland to Germany, which has a reputable industry suitable for the production of components. In the production, the substantial energy demand is from the engine production, which was estimated to be 4 kWh  (Saidani et al.
, 2021). All metals were assumed to require a metalworking process, while all plastics require injection molding. Aside from components, the assembly phase inputs include energy for processing, filters, and packaging. No transportation was modeled between component production and assembly, as the assembly factory was assumed to be located in the vicinity of the component factories. Regarding energy input, the electricity mix of Germany was used, and the assembly phase was assumed to require 5 kWh electricity  (Saidani et al. , 2021). Filters were assumed to be produced in Germany and sent 150 km by truck separately to the assembly factory, while the transportation of corrugated cardboard, the main component of the packaging, was included in the production dataset. After the lawn mower is assembled and packaged, it is dispatched to retailers in Sweden by truck, as illustrated in Fig.
Solution methods Since the developed mathematical model is categorized as a constrained mixed-integer nonlinear programming model, it is considered as an NP-hard problem, so achieving the exact solution for such a problem is difficult, if not say impossible, specifically when the size of the problem is big  [36]. However, the first attempt to solve the problem was to code the model in General Algebraic Modeling System (GAMS) and solve it using exact MINLP solvers such as BONMIN, DICOPT, and KNITRO. In order to transform the four objective functions given in equation (  4 )-(  7 ) into a single one, the   -metric method is used as a weighting scheme in this study  [51]. Using equation (  24 ), the method minimizes the differences between objective functions and their pertinent desired values ( *  ∈ R  ): Min 𝑍(𝑥) = [︁ ∑︀ 𝑄 𝑖=1 [︁ 𝑤 𝑖 ⃒ ⃒ ⃒ 𝑧 * 𝑖 -𝑧𝑖(𝑥) 𝑧 * 𝑖 ⃒ ⃒ ⃒ ]︁ 𝑝 ]︁ 1 𝑝 • (24) Subject to: 𝑥 ∈ 𝑋 ⊆ R 𝑄.
Experimental results All of the existing FLP benchmark datasets are designed for node-based location problems. To translate such benchmarks to edge-based instances, for each node one should consider a random number of edges to select directly connected nodes, random edge lengths, and random demands on each generated edge. There is no doubt that this would completely change the nature of the considered benchmark dataset. Thus, generating appropriate instances to evaluate the performance of applied algorithms would be inevitable in edge-based location problems. Using the random instance generation procedure and the Manhattan-metric method for normalized objective functions of equal weights explained in Section 3, the results of implementing the proposed algorithms on 16 randomly generated test cases of different sizes and specifications are shown in Table  5.
• Adaptation and elaboration of theoretical ontology considering the types of frauds: This stage provides us with a theoretical implementation of the concepts and sub concepts of the ontology, the section iterates the overview of the ontology. Adaptation of this approach is the key point to the successful development of the ontology. • Validation using datasets: The validation is proposed to help users to develop a confidence in the semantic content of the ontology. We use the dataset-based validation process due to the available resources and quality of the validation technique. We use various kinds of datasets for different types of frauds to validate the content of this ontology. • Discussion of results and improvement: This stage of the research work will consider the aim and objective of the research work, compared with the validation result.
3) Credit Card Fraud: Credit cards are one of the most famous targets of frauds but not the only one  [6]. Credit card fraud is a healthy and growing means of stealing billions of dollars from credit card companies, merchants, and consumers. Due to the rise and rapid growth of e-commerce, use of credit cards for online purchases have dramatically increased and it caused an explosion in credit card fraud. Credit cards become the most popular mode of payment for both online as well as regular purchase  [7]. In this research we investigate card fraud and the patterns used by the criminals to defraud the victims. Credit card fraud provides detailed ontological understanding of credit card fraud. From entities, terminologies, relations, instances as well as data types and classes, including card-not-present fraud, counterfeit, and skimming fraud, lost or stolen card fraud, and card-never arrived-fraud.
G. Transaction Fraud The transaction fraud was extracted from one of the datasets we obtained for the purpose of validating the ontology. Initially this concept of fraud was not in the ontology. We proposed transaction fraud to separate it from the payment fraud, which already exists in the ontology. The concept of transaction includes various sub concepts. From fake alerts, to fake items, items not delivered, service not rendered, etc. The properties of this concept are inline and related with various concepts and sub concepts of frauds in the ontology. Hence, it is one of the most relatively related concepts in this research.