dataesr/scientific-paragraphs-categorization huggingface dataset:
However, the results of Model 3 must be interpreted with caution, as this regression is prone to multicollinearity. 11 Additionally, we drop all financial firms in a second robustness check in Table  8. The results support our previous findings. Discount remains only significant in low transparency environments for both transparency variables. Furthermore, one might object that countries with disproportionately many observations could distort our results. With 235 observations in our main regression, Australian firms account for most equity rights offerings in our analyses, representing almost a quarter of our dataset. 12 Thus, we drop all firms from Australia in a further test in Table  9. As in the previous analyses, Discount is solely significant in low transparency environments. In a similar vein, we drop all observations from countries with less than five equity rights offerings (i.
However, there may exist some country-specific factors which we missed in our analysis, but which explain a large fraction of our dependent variable (CAR ). To avoid such a potential distortion of our results due to omitted factors, we perform this additional test. Table  11  presents our 11 Indicated by a mean variance inflation factor of 75. 68. 12 As described above and in Table  3 , we lose several observations from our original dataset due to missing variables. Hence, the number of firms from a certain country reported here and included in our regressions does not necessarily match the number of firms in our event study (Table  4 ). 13 As explained in the previous footnote, these countries might not coincide with the countries from Table  4  with less than five observations. Table  7  (continued) This table presents regression results for our OLS regression with CAR from a 7-day event window [-3;3] as the dependent variable.
We pursued a theoretical sampling approach within the two subsets to develop theoretical inferences for key dimensions (i. e. , capabilities) concerning the deployment of cloud-based product and service offerings. We contacted respondents purposively based on their professional positions and their potential abilities to address this study's questions  [51, 56]. In consequence, the combination of a priori contrasting sampling subsets of large and small vendors and successive theoretical sampling of respondents within the selected software vendors helps to improve the validity of our findings, as these procedures ensure to comprehensively examine possible variations or replications in data patterns deriving from the distinct cases  [51, 54]. As a result of our sampling procedures, we collected evidence from 10 software vendors that provide cloud solutions in Germany and Austria.
Acknowledgments Jose Benitez  would like to express his gratitude for the research sponsorship received from the  European Regional Development Fund (European Union ) and the  Government of Spain  (Research Project  ECO2017-84138-P ), the  Regional Government of Andalusia  (Research Project  A-SEJ-154-UGR18 ), the  Endowed Chair of Digital Business Transformation at Rennes School of Business , and the  Slovenian Research Agency  (Research Core Funding No. P5-0410 ).
technological capabilities. "Cloud solutions are highly C. 3) The integration and specialized solutions. management of security Especially when there is a high competencies are crucial for fluctuation of resource the cloud computing-based requests, some internal experts business model innovation. are needed" (CEO of company B). "The knowledge and the expertise by taking care of that many databases are huge. We are better prepared for any attack than the companies, which have to take their data onto their servers themselves" (Product Manager of company A). Business flexibility D. 1) Transition toward "When we talk about cloud (D) efficient online sales and computing and a cheap marketing structures based product, usually you do not on cloud technology. have a sales representative, just D. 2) The promotion of a a few.
Applied studies of systems-focused cost estimation are described in the literature  [10]  [11]  [12] , of these, COSYSMO  [12]  is a parametric model deriving from cost modelling theory applied to both product development and software projects. This model evaluates a system by calculating the person-months required to develop it from 'size drivers' and 'cost drivers', coefficients that estimate the complexity of the system. This model also features in the commercial systems engineering cost estimation tools SEER-H and SEER-SYS from Galorath Inc. [13] , assimilating with aforementioned product and service cost models. A blind validation study comparing the former with a competing tool found it had an average error of 23% estimating the cost of twelve NASA science missions, comprising the project management, systems engineering, safety and mission assurance, payload, spacecraft bus, and systems integration and test components  [14].
Data Analysis and Interpretation We started the data analysis process by transcribing the interviews, resulting in 293 single-spaced pages of text. Next, we coded the data in three consecutive stages: open, axial, and selective  (Strauss and Corbin 1998 ). An illustration of the coding process is provided in Table  2. Using the MAXQDA software (version 2016), two of the authors independently performed open coding, identifying initial concepts in the data and grouping them into categories  (Gioia, Corley, and Hamilton 2013). Following  Gioia, Corley, and Hamilton (2013) , we strived "to adhere faithfully to informant terms" and relied on in-vivo or descriptive codes. Based on  Perreault and Leigh (1989) , we then assessed inter-judge reliability between the two researchers. Despite slight differences in tagging, the codes pointed to nearly identical meanings.
Our insights resonated well with existing research, suggesting that service growth strategies of product-centric B2B companies require a fundamental shift on organizational culture  (Kohtamaki et al. 2015; Kowalkowski and Ulaga 2017; Mathieu 2001). Our interviews revealed that resistance to F2F initiatives emerged not only among frontline employees and middle management but also at the senior management level. As one informant explained: "At the beginning, even our board members were reluctant to charge for these free services (real-time databased insights), saying, 'Wait a minutewe are a product company. Are we moving to service business or what?' It took quite some time and effort to make them realize we are not changing our business altogether, and we were already providing those services for free and losing money! It took some effort to get the 'go ahead' from them.
Acknowledgment The authors express their sincere gratitude for the helpful comments in developing the present article to  Ajay Kohli ,  Andreas Eggert ,  Gary Lilien ,  Nicole Coviello ,  Niina Nummela ,  Shantanu Dutta ,  Tuure Tuunanen , and the session participants at the  BMM-EMAC Conference  ( 2017 ), the  AMA Winter Academic Conference  ( 2018 ), and the  ISBM Academic Conference  ( 2018 ). The continuous support and the constructive suggestions from the editor, the associate editor, and the anonymous reviewers throughout the review process are gratefully acknowledged. Mekhail Mustak acknowledges the financial support from the  Foundation of Economic Education, Finland , and the  Kone Foundation, Finland.
To ensure that the conclusions reached by case studies are valid the information they collect must be triangulated by comparing data, testimonies, and theories from several independent sources. While using a wide range of cases enables researchers to adopt a more comprehensive approach and provide more nuanced insights, valid conclusions can be drawn from a limited number of cases. We selected the systems examined in this study because they corresponded closely to the missions described in the literature review and because of their reputation with professionals. (1) Synertrade is a purchasing management software package that develops automated processes. (2) Silex is a matching system that automatically links purchasing requests to the most appropriate suppliers. (3) SAP Ariba is data analysis and decision support software that proposes the best choices to purchasers.
(4) Jaggaer promotes collaborative, lasting supplier relations. (5) Ideapoke facilitates technology capture and the implementation of innovative projects. The use of a range of diverse sources enabled us to enrich and triangulate the information  (Denzin & Lincoln, 2011). For each case we based the data collection on: a documentary analysis of websites, brochures and presentation videos; non-participant observation of the platform's operations; and the testimony of a buyer who uses the software regularly. Companies that have adopted AI in their purchasing departments provide opportunities for observation, analysis, and interpretation  (Miles & Huberman, 1994). Exploration techniques are preferable to experimentation for the observation of natural, everyday behaviors, and the collection of authentic data about actual practice.
The Synertrade automated purchasing processes system Synertrade Accelerate is a modular software that manages and optimizes purchasing processes. A leader in digital procurement solutions, Synertrade has recently been recognized by Qlik (a US-based data analytics platform) as "EMEA OEM Partner of the Year" for 2019. Awarded annually, these awards recognize excellence in Qlik's partner community, in various categories, both globally and in key regions. Synertrade was recognized, among the international network of Qlik partners, for its expertise in strategic purchasing, combined with the ever-increasing involvement of its technical experts. It assists buyers at every stage in sourcing, procurement, supplier integration and evaluation, performance monitoring, and joint project management. Synertrade Accelerate encompasses a portfolio of 35 applications divided into five essentially operational and tactical sub-sets.
The system produces statistics on AI adoption and user behavior, and enables firms to implement risk management policies. (5). Idea to Product is a project management module that, through managing internal and external collaborations, helps firms select and introduce innovations. It uses applications for communication, planning, resource management, and process optimization. It provides better traceability, reduces project duration, increases project success rates, and standardizes processes. The Synertrade Accelerate platform now incorporates Commodity-Bots, virtual intelligent robots that supervise purchasing processes and the data collected by its different applications and notifies buyers of opportunities or any relevant issues. An intelligent agent, named Marvin, is available to serve buyers, answer their questions, and find information.
The platform also claims that it can anticipate digital disruptions and their impact on consumer behavior and industrial competitors. Ideapoke is based on a matching system that does not focus on sourcing and procurement, but on ideas, vision, projects, and innovation. Buyers can, thus, use it to introduce novel technologies, co-develop innovations, diversify, and conquer new markets. The system enables companies to make sense of the confusing, overabundant information that makes it difficult to identify relevant data and appropriate partners. Moreover, all the accurate, usable information about technologies cannot be accessed using traditional research tools, given that it exists in a wide range of forms and throughout countless networks and spaces. It is exceedingly difficult to distinguish between technologies with real commercial potential and experimental technologies that have no practical uses.
Interdependence with other departments Some advantages of AI are that it provides an overall approach to every department and stakeholder, considers an enormous number of parameters, and can then simulate new business models that take into account different types of organization, available resources, and potential profits. While the purchasing department is at the heart of this process, since it is cross-functional, open to the environment and proactive, AI-based initiatives will quickly become limited if they are led only by purchasers. Ideapoke, for example, highlights its coordination capacity in the following statement taken from its website: "[Ideapoke] redefines the way organizations innovate by providing software tools and a business platform to access the world's technology information easily, connect with technology experts, and collaborate with technology partners.
RESEARCH APPROACH Toward understanding environmental performance, our research question is: How to characterize and improve the environmental performance of an infrastructure design project? The first part of this paper exerts a systematic literature review  (Garza-Reyes, 2015)  on the concept of performance, and then environmental performance, as well as its dimensions using databases such as Web of Science and Google Scholar. The keyword search applied to title is: performance, environmental performance, sustainable projects, construction projects, infrastructure projects, railway, sustainability, and eco-design. The selection excludes all articles that are not written in English or French; the title should not be oriented to a specific environmental technology. Finally, the choice is based on the abstract reading.
Research design overview Given the exploratory nature of this research, a qualitative methodology was employed based on consumers' narratives of their SSRT use to investigate research questions RQ1 and RQ2, and to validate the extended conceptualization of consumer psychological empowerment proposed in Fig. 1. Further, to examine research questions RQ3 and RQ4 about SSRT paradoxes, we carried out a lexicometric exploration of survey data targeting the empowerment themes previously identified in the verbatim narratives. Forming part of inductive quantitative methods, lexicometric approaches applied to interview data are useful to provide key insight into linkages between textual variable categories that might not be identified using manual coding  (Haynes et al. , 2019) , but might explain paradoxical relationships.
Narrative data collection and analysis Open-ended in-depth interviews were employed to collect consumers' narratives about their use of self-scanning and self-checking devices. These two prominent instances of SSRTs were checked as prototypical in a preliminary study, and were then systematically assigned the main object of consumer narratives. Previous qualitative research has generally investigated self-service contexts through focus groups or semi-structured interviews to understand user motivations and the role of situational factors  (Essén et al. , 2015). In contrast, consumer narratives are decentered methods that consider the consumer an active producer of his or her experience  (Holt, 2002). To the extent to which they help individuals develop a reflexive view of their consumption, narratives allow researchers to understand how individuals derive meaning and negotiate their self-construction from consuming artifacts or brands  (Holt, 2002).
11). As an everyday life practice, the use of retail devices may require minimal attention to be accomplished. Therefore, a projective approach is useful to allow individuals to envision aspects of the phenomenon that are not easily accessible. Our projective visuals comprised pictures of self-scanning devices near the store entrance and self-checkouts at the exit of a supermarket. To avoid gender bias, pictures alternated between male and female consumers using self-scanning or self-checking terminals. In line with the methodological approach of  Weinberger, Zavisca, and Silva (2017) , the recruitment of participants involved a combination of two sets of in-depths interviews. Following  Pelletier and Collier (2018) , our primary data set purposefully obtained a diverse representation of SSRT experiences through a convenience sample based on a selection criterion.
Six respondents were selected using the criterion of their attitude valence toward  SSRT (i. e. , positive, neutral, negative). From the first data set analysis, a core theoretical construct of empowerment themes emerged. To achieve thematic saturation, a second dataset of seven additional respondents was recruited through snowball sampling, using the stopping criterion approach  (Francis et al. , 2010)  to determine the adequate sample size. In the case of qualitative studies aimed at populating pre-specified theoretical constructs, such as the extended empowerment framework, the stopping criterion targets three consecutive interviews in which no new themes emerge, for deciding the saturation point. Two investigators participated in the coding process and analyzed the data through a constant comparison method.
The verbatim transcripts consisting of 95 pages were subjected to a theory-driven thematic analysis from a deductive approach described by  Braun and Clarke (2006, p. 12). While our extended model of consumer psychological empowerment was largely expected to inform the coding matrix, the qualitative data interpretation remained open to new categories or subcategories inferred from consumer narratives throughout the overall analysis. Based on the stopping criterion, both the investigators agreed that the thematic saturation was achieved in the second dataset after seven additional interviews, with no new empowerment themes emerging in the last three ones. The final sample, which exhibits a size similar to the other theory-driven qualitative studies, investigating consumer contexts  (Francis, 2010; Saunders et al.
Lexicometric study Following the thematic analysis, a survey approach was employed to determine the extent to which consumers shared the empowerment themes associated with the use of SSRT. Data were drawn from an opt-in online panel, supplied by the market research agency, Toluna. The sample was balanced on all major demographics (gender, age, education, and occupation) to mirror the adult population under investigation. After being exposed to the same projective visuals used for the narrative collection, respondents were asked to read the definition of each SSRT-based psychological empowerment theme and to indicate on a 2point scale (yes/no) whether it corresponded to their own perceptions. Our final sample consists of 201 respondents and is described in Table  3. Based on the sample's dichotomous responses, we then conducted a lexicometric analysis  (LoMonaco et al.
Consequently, in the final graph, the edges uniting the empowerment themes as nodes reveal the strength of the relations of similarity measured by the Jaccard coefficient, thus providing a pattern of significant paths among empowerment themes. In this pattern, a theme is considered a major node within the maximum tree depending on its connectivity, i. e. , the number of total links with other elements and the strength of such relations. As a third step, thematic communities were identified within the maximum tree, using the edge-betweenness algorithm  (Newman & Girvan, 2004) , operated by the software Iramuteq. This optimization algorithm identifies communities within a given network structure by finding and sequentially removing edges with the highest betweenness, where betweenness is a quantity that favors edges that lie between communities and disfavors those that lie inside communities.
This study offers relevant and rigorous research output that is practice oriented and extends the knowledge base. Our theoretical model is grounded in Knowledge Management Theory (KMT) and the model has been statistically validated using B2B data from South Africa. The data was collected from mining industry. Technological change and changing consumer behaviour have emerged as a major concern for the mining industry. The South Africa mining industry is in transition from a conventional mining environment to a mechanised shallower, technologically advanced industry. To stay competitive mining companies are adopting digitalisation as a basic part of their new business model encircling all functions: supply chain, marketing and sales and in particular interactions with current and potential customers.
Knowledge Management Theory (KMT) Knowledge management is a popular strategy to enhance the competitive position of an organisation  (DeTienne & Jackson, 2001; Dwivedi et al. , 2011). Organisational learning can aid in building new knowledge or providing insights that can change behaviour  (McElroy, 2000). Knowledge can be either explicit or tacit. Explicit knowledge is knowledge that has already been documented in some form (files, databases, manuals, etc. ), whereas tacit knowledge is present only among employees and considered an important knowledge resource in any organisation. Through accessing, sharing and adopting both explicit and tacit knowledge, an organisation can dramatically enhance performance  (DeTienne & Jackson, 2001). In the 21 st century, knowledge has proven to be an important part of production.
Sample selection We used an online survey with samples from the mining and mineral processing industry in South Africa. The sample for the pilot survey and final survey was established based on random sampling from Directory No. D1/2016 "Operating mines and quarries and mineral processing plants in the Republic of South Africa, 2016" Directorate of Mineral Economics. This database was compiled by Ms M C Lourens, and the 25 th revised edition was published in January 2016 and considered in our study. In WarpPLS two methods are used to estimate minimum required sample sizes, the inverse square root and gamma-exponential methods  (Kock and Hadaya, 2018). The "statistical power and minimum sample size requirements" analysis indicates 655 samples as per the inverse square root method; and 647 samples as per the gammaexponential method.
Non-response bias The primary data was received in two phases. One set of responses was received before follow-up and the second set was received after doing follow-up with the potential respondents. The early wave (120 responses) and the late wave (187 responses) were compared using Levene's test to check for non-response bias  (Armstrong and Overton, 1977). Levene's homogeneity of variance test was conducted to check whether the distribution of our variables changed depending on the wave. SPSS software was used to compare means and perform the analysis by selecting one-way ANOVA to check the Levene statistic. The research team found that none of the values were significant, which means there was no difference between the waves.
The research team decided to use partial least squarebased structural equation modelling (PLS-SEM). WarpPLS software was chosen to run the analysis. WarpPLS was invented by Ned Kock  (Kock, 2012) , and as the software is very user friendly, it has become quite popular in a very short period of time. WarpPLS-based analysis has been used previously by leading researchers in the field of management, and their work has been accepted in top ranked journals (e. g. ,  Dubey et al. 2019 a,b; Wamba et al. , 2017). Scientific debate over the use of CB-SEM or PLS-SEM is still ongoing. However, simple guidelines were set forth by  Preacher and Hayes (2008)  and  Hair et al. (2017)  to select the right technique depending on the nature of the research work. The research team met the criteria as suggested by  Hair et al.