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Usually, test automation scripts for a web application directly mirror the actions that the tester carries out in the browser, but they tend to be verbose and repetitive, making them expensive to maintain and ineffective in an agile setting. Our research has focussed on providing tool-support for business-level, example-based specifications that are mapped to the browser level for automatic verification. We provide refactoring support for the evolution of existing browser-level tests into business-level specifications. As resulting business rule tables may be incomplete, redundant or contradictory, our tool provides feedback on coverage.

Usually, test automation scripts for a web application directly mirror the actions that the tester carries out in the browser, but they tend to be verbose and repetitive, making them expensive to maintain and ineffective in an agile setting. Our research has focussed on providing tool-support for business-level, example-based specifications that are mapped to the browser level for automatic verification. We provide refactoring support for the evolution of existing browser-level tests into business-level specifications. As resulting business rule tables may be incomplete, redundant or contradictory, our tool provides feedback on coverage.

If you are a manager who receives the results of any data analyst’s work to help with your decision-making, this book is for you. Anyone playing a role in the field of analytics can benefit from this book as well. In the two decades the editors of this book spent teaching and consulting in the field of analytics, they noticed a critical shortcoming in the communication abilities of many analytics professionals. Specifically, analysts have difficulty in articulating in business terms what their analyses showed and what actionable recommendations were made. When analysts made presentations, they tended to lapse into the technicalities of mathematical procedures, rather than focusing on the strategic and tactical impact and meaning of their work. As analytics has become more mainstream and widespread in organizations, this problem has grown more acute. Data Analytics: Effective Methods for Presenting Results tackles this issue. The editors have used their experience as presenters and audience members who have become lost during presentation. Over the years, they experimented with different ways of presenting analytics work to make a more compelling case to top managers. They have discovered tried and true methods for improving presentations, which they share. The book also presents insights from other analysts and managers who share their own experiences. It is truly a collection of experiences and insight from academics and professionals involved with analytics. The book is not a primer on how to draw the most beautiful charts and graphs or about how to perform any specific kind of analysis. Rather, it shares the experiences of professionals in various industries about how they present their analytics results effectively. They tell their stories on how to win over audiences. The book spans multiple functional areas within a business, and in some cases, it discusses how to adapt presentations to the needs of audiences at different levels of management. 1. Know Your Audience Subhashish Samaddar and Satish Nargundkar 2. Presenting Results from Commonly Used Modeling Techniques Subhashish Samaddar and Satish Nargundkar 3. Visualization to Improve Analytics Jennifer Lewis Priestley 4. Marketing Models-Demonstrating Effectiveness to Clients Gregg Weldon 5. Restaurant Management: Convincing Management to Change William Swart 6. Project Presentation in the Armed Forces Lynette B. Arnhart 7. Inventory Management: Customizing Presentations for Management Layers Elyse Hallstrom 8. Executive Communication in Process Improvement Keith E. Miller 9. Internal Auditing: Seeking Action from Top Management to Mitigate Risk Jason R. Togmartin 10. Consumer Lending: Winning Presentations to Investors J. P. James 11. \"As You Can See...\" Subhashish Samaddar and Satish Nargundkar Subhashish Samaddar , PhD, Certified Analytics Professional (CAP ® ), is a professor of business analytics and operations management in the managerial sciences department of the J. Mack Robinson College of Business at Georgia State University, Atlanta, Georgia, where he was the founding academic director of MS analytics program. He served on the INFORMS' team that created the CAP certification examination administered globally and coedited its first guide book. An internationally reputed and multiple award-winning researcher, teacher, and speaker, he specializes in business analytics, operations and organizational knowledge management, and decision­ making. A veteran of more than 25 years and a consultant in analytics, he has helped many U.S. organizations-Fortune 100, privately held and governmental agencies-with their analytical needs. He currently teaches business analytics and research methods to undergraduates, MBA and executive master's and doctoral students, and corporate clients. Satish Nargundkar, PhD , is a professor of business analytics in the J. Mack Robinson College of Business at Georgia State University, Atlanta. Over the past three decades, he has helped large and small companies improve their decision-making through analytics. A recipient of multiple awards for teaching and research, he has over 25 years of experience in the areas of analytics, process improvement, and decision support. His research interests are multidisciplinary and include supply chain management, quantitative methods, and the improvement of teaching methods. He is passion­ ate about excellence in teaching and is sought after as an instructor in executive programs. In his spare time, he enjoys reading, traveling, and photography, and is an instructor in martial arts.

Selection and proper application of business process modeling methods and techniques have a significant impact on organizational improvement capabilities as well as proper understanding of functionality of information systems that shall support activity of the organization. A number of business process modeling notations were implemented in practice in recent decades. Most significant of the notations include ARIS, Business Process Modeling Notation and several Unified Modeling Language (UML) extensions. In this paper, the assessment whether one of the most flexible and strictly standardized contemporary business process modeling notations, i.e. Rational UML Profile for Business Modeling, enable business analysts to prepare business models that are all-embracing and understandable by all the stakeholders. After the introduction, methodology of research is discussed. The following section presents selected case study results.

PurposeThis study aims to examine the relationship between institutional logics and specifications quality, and how this relationship is mediated by the legitimacy of the procurement process and stewardship behaviour.Design/methodology/approachThis study draws on insights from institutional logics theory, and legitimacy and stewardship behaviour literature. We conducted an extended literature review to gain a comprehensive understanding of “institutional logics” and their manifestations in organizational contexts, utilizing the 2000–2024 data collected from the EBSCO, Scopus and Web of Science databases, complemented with Google Scholar. We gather that institutional logics manifest in several forms, and that while some organizations may thrive on a single logic, in certain contexts institutional logics can manifest in combinations – “multiple logics or hybrids”. Based on this understanding, we developed testable research hypotheses, predicting the influences of institutional logics – professional logic, efficient service logic and delivery (market) logic, on legitimacy, stewardship behaviour and specifications quality. We then carried out an empirical study, adopting a quantitative cross-sectional survey design with a self-administered questionnaire to test the hypothesized relationships. The empirical data were obtained from 162 procuring and disposing entities in Uganda and analyzed using the partial least squares structural equation modelling technique.FindingsThe study findings reveal that institutional logics exert a strong positive effect on the legitimacy of the procurement process and on stewardship behaviour, which, in turn, both positively influence specifications quality.Research limitations/implicationsThe study findings have implications for theory and practice. The study findings provide useful insights that support the conceptual and theoretical development of institutional logics theory and applications in procurement literature. In addition, the study findings enhance procurement managers’ understanding of the mechanisms through which institutional logics can foster specifications quality. However, considering the fact that the study was conducted in a single country context, and focused on the public sector only, the findings of the study might not be generalizable globally.Originality/valueThis study contributes to established knowledge about quality management and procurement by examining the legitimacy of the procurement process and stewardship behaviour of those involved in procurement processes as mechanisms through which procuring entities are able to use institutional logics to enhance specifications quality. In addition, the study highlights areas for future research that may be explored to increase understanding of the value of institutional logics in ensuring specifications quality, and the link between specifications quality and the general performance of procuring entities.

A sustainable and reliable machining process is the main goal of seeking machine digitization. Artificial Intelligence (AI), and Cyber-Physical System (CPS) combined with Artificial Intelligence are used for process control. This has become more essential in the case of machining of high-cost aerospace materials and critical product specifications. In this paper, a novel self-healing mechanism was developed to recover a CNC machine from producing parts that do not conform, to surface roughness’s specifications. The machine settings are reconfigured autonomously and online to recover from the effect of tool wear and to keep the surface roughness within the design specifications. The proposed self-healing mechanism is based on a pattern recognition algorithm called Logical Analysis of Data (LAD). This algorithm generates patterns that characterize the out-of-specification state, and provides a corrective setting within the recovery patterns of the within-specification state by using various distance approaches. The developed self-healing mechanism is composed of three modules: CPS model of the CNC machine (module 1), classification into, out of, or within-specification states (module 2), and a self-healing controller (module 3) that is activated if the state of out-of-specification is found by module 2. The three modules are software. The current hardware system of the machine is not altered. The proposed self-healing is applicable and integrable to CNC machines with a wide range of machining parameters of feed rate from 20 mm/min to 750 mm/min and spindle speed from 15,000 RPM to 35,000 RPM. To validate the developed mechanism, a deep learning artificial model was developed on physical data to emulate the CNC milling machine in a CPS simulation environment, and test runs were executed. The proposed self-healing mechanism was evaluated under several simulation runs that covered the ranges of CNC machine settings. The measure of performance of the proposed mechanism is the out-of-specification clearing time. The test runs show that the proposed self-healing mechanism was able to clear the out-of- specification state and to recover the within-specification state in less than five seconds, with the best distance metric approach. The results of the time response for each test run are reported.

We introduce Spectra, a new specification language for reactive systems, specifically tailored for the context of reactive synthesis. The meaning of Spectra is defined by a translation to a kernel language. Spectra comes with the Spectra Tools, a set of analyses, including a synthesizer to obtain a correct-by-construction implementation, several means for executing the resulting controller, and additional analyses aimed at helping engineers write higher-quality specifications. We present the language in detail and give an overview of its tool set. Together with the language and its tool set, we present four collections of many, non-trivial, large specifications, written by undergraduate computer science students for the development of autonomous Lego robots and additional example reactive systems. The collected specifications can serve as benchmarks for future studies on reactive synthesis. We present the specifications, with observations and lessons learned about the potential use of reactive synthesis by software engineers.

We synthesize two related literatures on firm-level drivers of wage inequality. Studies of rent sharing that use matched worker-firm data find elasticities of wages with respect to value added per worker in the range of 0.05–0.15. Studies of wage determination with worker and firm fixed effects typically find that firm-specific premiums explain 20% of overall wage variation. To interpret these findings, we develop a model of wage setting in which workers have idiosyncratic tastes for different workplaces. Simple versions of this model can rationalize standard fixed effects specifications and also match the typical rent-sharing elasticities in the literature.

The concept of entrepreneurial ecosystems has quickly established itself as one of the latest 'fads' in entrepreneurship research. At face value, this kind of systemic approach to entrepreneurship offers a new and distinctive path for scholars and policy makers to help understand and foster growth-oriented entrepreneurship. However, its lack of specification and conceptual limitations has undoubtedly hindered our understanding of these complex organisms. Indeed, the rapid adoption of the concept has tended to overlook the heterogeneous nature of ecosystems. This paper provides a critical review and conceptualisation of the ecosystems concept: it unpacks the dynamics of the concept; outlines its theoretical limitations; measurement approaches and use in policy-making. It sets out a preliminary taxonomy of different archetypal ecosystems. The paper concludes that entrepreneurial ecosystems are a highly variegated, multi-actor and multi-scalar phenomenon, requiring bespoke policy interventions.

Institutions have a decisive impact on the prevalence and nature of entrepreneurship. To date, the impact of institutions on (productive) entrepreneurship and the effects of entrepreneurship on economic growth have largely been investigated in isolation. In this paper, we bring together institutions, entrepreneurship, and economic growth using a parsimonious growth model in a 3SLS specification. In our first stage, we regress multiple measures of entrepreneurial activity on institutional proxies that are known to correlate with more productive forms of entrepreneurial activity. Using the fitted values of this first-stage regression as our proxy for productive entrepreneurship, we can then estimate a panel growth regression following Islam (1995) in a second stage. The third stage then optimizes the estimation of the two equations simultaneously. Our results show that productive entrepreneurship contributes to economic growth. In our set of proxies for institutional quality, financial stability, small government, and perceived start-up skills are the most important predictors of such productive entrepreneurship.