Investigation of Innovation In Wine Industry Via Meta-Analysis

This study provides a systematic review of 76 relevant wine business studies published in the last 30 years. Our meta-analysis investigates six commonly used variables to explain wine innovation: absorptive capacity, technology adoption, sustainable practices, export orientation, firm size, and firm age. We also investigate the association between innovation and financial performance, using the reported effect sizes in the literature. Our meta-analysis reveals that absorptive capacity, technology adoption, sustainable practices, export orientation, and firm size positively correlate with innovation efforts, and innovation is positively associated with financial performance. However, we find no correlation between firm age and innovation. In addition to the meta-analysis, we apply basic text analytics and narrative review methodologies to identify a taxonomy of wine industry innovation according to four types of innovation. Based on our systematic literature review results, we make a series of managerial and policy recommendations for wine firms. Finally, we identify gaps in the literature and suggest future research directions

Regulations and software evolution: An example from the military domain

AbstractIn this article, the impact of regulatory changes on software development is assessed in the context of military standards. A previously conducted experiment incorporating three standards is further investigated for this purpose, outlining the characteristics of the evolution in standards and its effects. In addition to this experiment that was designed with projects conducted as graduate class work, a real project from the industry is utilized, to demonstrate the similar effects of the evolution as discovered in the earlier experiment. Finally, the results of the assessment are generalized and a forecast is presented for the next potential regulation change, the IEEE Std 12207-2008

Outsourcing, managing, supervising, and regulating private military companies in contingency operations

This thesis examines the utilization of private military companies (PMCs) by government agencies of the United States in contingency operations in Iraq and Afghanistan. The aim of this thesis is to investigate the roles that PMCs play in current contingency operations, and to analyze how PMCs can become more useful instruments in contingency operations if they are properly outsourced, managed, supervised, and regulated. In this regard, this study largely rests on transaction cost economics to explain the logic of outsourcing from governmental agencies' perspectives. On the other hand, principal-agent theory and new institutionalism provide the theoretical basis of using effective oversight mechanisms to exert better control over the activities of PMCs in contingency operations. This thesis recommends the United States, Iraq, and Afghanistan use the Montreux Document as a guide to better regulate PMCs in contingency operations.http://archive.org/details/outsourcingmanag109455171Turkish Army authorApproved for public release; distribution is unlimited

Computing Cyclomatic Complexity with Cubic Flowgraphs

Two new methods for the computation of cyclomatic complexity especially for decomposable representations are introduced. Building software by integration is a developing paradigm, especially enabled by the emerging component technologies. Decomposition of the design for a top-down approach is a prerequisite for this paradigm. Cubic flowgraphs are instrumental in providing formalisms for decomposition and integration. Cyclomatic complexity analysis of a design representation that is decomposable is the goal of this research. In addition to introducing cyclomatic complexity computation using cubic flowgraphs, preservation of cyclomatic complexity in the decomposition of the cubic flowgraph is also presented

Adaptive Appointment Scheduling for Patient-Centered Medical Homes

Incorporating patient-centered medical home (PCMH) principles, we develop an adaptive appointment scheduling model for a primary care setting. We propose a simulation optimization approach to sequentially schedule appointments to provide desirable schedules from the perspective of both patients and the medical practices. The objective minimizes the weighted expected cost of patient direct and indirect waiting time, physician idle time, and physician overtime. Our efficient data-driven algorithm considers patient preferences and future appointment requests, while employing overbooking to mitigate patient related uncertainties, such as no-shows and lateness. Benchmarking against myopic and optimal algorithms, computational results show that the adaptive scheduling approach provides significant value. The adaptive method provides considerable cost savings even under conditions of high patient uncertainty. In addition, the method produces high quality solutions in little time, thus providing a viable tool for practice

AI In Operations Management: Applications, Challenges and Opportunities

We have witnessed unparalleled progress in artificial intelligence (AI) and machine learning (ML) applications in the last two decades. The AI technologies have accelerated advancements in robotics and automation, which have significant implications on almost every aspect of businesses, and especially supply chain operations. Supply chains have widely adopted smart technologies that enable real-time automated data collection, analysis, and prediction. In this study, we review recent applications of AI in operations management (OM) and supply chain management (SCM). Specifically, we consider the innovations in healthcare, manufacturing, and retail operations, since collectively, these three areas represent a majority of the AI innovations in business as well as growing problem areas. We discuss primary challenges and opportunities for utilizing AI in those industries. We also discuss trending research topics with significant value potential in these areas

Enhancing UML Connectors with Behavioral ALF Specifications for Exogenous Coordination of Software Components

Connectors are powerful architectural elements that allow the specification of interactions between software components. Since the connectors do not include behavior in UML, the components include the behavior for coordinating the components, complicating the designs of components and decreasing their reusability. In this study, we propose the enrichment of UML connectors with behavioral specifications. The goal is to provide separation of concerns for the components so that they are freed from coordination duties. The reusability of the components will increase as a result of such exogenous coordination. Additionally, using the associated behaviors, we aim to resolve the ambiguities that arise when n-ary connectors are used. We use a series of QVTo transformations to transform UML models that include connector behaviors in ALF specifications into UML models which include fUML activities as connector behavior specifications. We present a set of example connectors specified using the proposed method. We execute the QVTo transformations on the example connectors to produce models that represent platform-independent definitions of the coordination behaviors. We also present and discuss cases from real-life large-scale avionics software projects in which using the proposed approach results in simpler and more flexible designs and increases component reusability

On Kantorovich process of a sequence of the generalized linear positive operators

WOS: 000256972400005We define the Kantorovich variant of the generalized linear positive operators introduced by Ibragimov and Gadjiev in 1970. We investigate direct approximation result for these operators on p-weighted integrable function spaces and also estimate their rate of convergence for absolutely continuous functions having a derivative coinciding a.e., with a function of bounded variation