Digital Entrepreneurship

A comprehensive guide to digital entrepreneurship, bridging academic research and industry practice. Morabito provides a strategic overview of the main challenges and trends related to digital entrepreneurship, structured in three parts. Part I focuses on strategy and management issues, guiding readers through the theory and practice of building, implementing and growing new digital ventures and outlining the skills that are necessary for digital entrepreneurs to succeed and lead. Part II focuses on digital business systems, describing the main technological aspects that support and comprise the core infrastructure for digital entrepreneurship, including social media and the Internet of Things. Finally, Part III provides analyses of three core industries in which digital ventures are particularly important: fintech, manufacturing and fashion. Digital Entrepreneurship will appeal to students and researchers in the areas of digital strategy/innovation and information systems management. It will also be of interest to practitioners looking to develop or innovate digital ventures.

Investigating performance of transformer health index in machine learning application using dominant features

Transformer Health Index (HI) has become a standard tool for performing transformer health evaluations. Due to economic constraints, the recently published paper focuses on developing various techniques to identify the most dominant features for transformer HI prediction. However, the fundamental problems concerning their input features remain unresolved since most suggested features contradict industry practice. In this paper, the primary objective is to investigate the performance of the transformer HI by developing and utilizing only dominant features following the industry recommendation. The investigated dominant features in this paper using 1) CO2/CO ratio and 2) the Incipient fault for detecting temperature abnormalities, and 3) the Dissipation Factor (DF) for detecting oil contamination. The performance validation is carried out using various machine learning (ML) classifiers. Also, the performance of the ML model is validated based on 10-fold type cross-validation to avoid biases in the experiment. As a result, the proposed Artificial Neural Network (ANN) network utilizing the investigated dominant features following the industry practice has produced the highest average accuracy of 80.09% than others ML techniques as a classifier. Hence, additional studies to complement the investigated dominant features may be considered for the subsequent investigation.

Mass Customization and the “Parts-Procurement Planning Problem”

We study a new parts-procurement planning problem that is motivated by a global auto manufacturer (GAM) that practices mass customization. Because of the astronomically large number of producible configurations, forecasting their demand is impossible. Instead, firms forecast demand for options that constitute a vehicle. Requirements for many parts (up to 60%) are based on the combinations of options in a fully configured vehicle. The options’ forecast, however, does not map into a unique configuration-level forecast. As a result, the options’ forecast translates into ranges for many parts’ requirements. The combined ranges of a set of parts are not always equal to the sum of the component ranges; they may be less. Determining parts ranges is a large-scale NP-hard problem. Large ranges and inaccurate calculation of these ranges can result in excess inventories, shortages in inventories, and suboptimal flexibility levels. We model and analyze the problem of allocating parts to suppliers and accurately computing the ranges to minimize procurement costs arising because of ranges. The range costs are assumed to be convex increasing. We perform extensive numerical analysis using a large set of randomly generated instances as well as eight industrial instances received from GAM to establish the quality of our approximation framework. Our proposed approach significantly reduces the error in range estimates relative to current industry practice. In addition, the proposed approach for allocations of parts to suppliers reduces joint-parts ranges by an average of 29.87% relative to that of current practice. This paper was accepted by Jeannette Song, operations management.

Reframing culture: Stuart Cunningham's legacies

This essay offers an appreciation of Stuart Cunningham's substantial and diverse contributions to ‘reframing culture’ in Australian research, policy and industry practice, from his early reformulations of Australian film history to his recent work on digital media disruption. The essay discusses the range of Cunningham's institutional and intellectual legacies, suggesting that his advocacy for cultural policy and the creative industries together with his leadership of major collaborative research initiatives in the humanities and social sciences have been especially important for media and cultural studies in Australia. Further, his approach to the project of ‘reframing culture’ is likely to remain a critical task.

A Research-Based Approach to Game Writing Pedagogy

This paper discusses the importance of, and presents a possible framework for, phenomenological research of game industry practice to enhance pedagogy in computer game design (CGD) education. Built around examples from one such study on the practices of game industry writers, the author provides background for the study in question, outlines the theoretical framework of the research design, and presents an overview of the findings. A discussion of possible impacts and further applications in other subdisciplines of game development follows.

A comprehensive survey of industry practice in real-time systems

This paper presents results and observations from a survey of 120 industry practitioners in the field of real-time embedded systems. The survey provides insights into the characteristics of the systems being developed today and identifies important trends for the future. It extends the results from the survey data to the broader population that it is representative of, and discusses significant differences between application domains. The survey aims to inform both academics and practitioners, helping to avoid divergence between industry practice and academic research. The value of this research is highlighted by a study showing that the aggregate findings of the survey are not common knowledge in the real-time systems community.

Responding to the Impact of the COVID-19 on Food Value Chains – Case of Industry Practice

Supply chain operations in food value chains includes all logistics activities that enable the flow of agriculture inputs, outputs, and agriculture-related services, such as transportation, warehousing, procurement, packaging and inventory management. The efficacy of logistics is critical for the agri-food sector, in particular in times of crisis. Disruptions can cause adverse impacts on the quality of food, freshness, its safety, and can impede access to markets and affordability. The COVID-19 pandemic caused that the governments around the world implemented different measures, including a reduction in the transportation of goods (ground, ocean freight and air freight), as well as migration of labour domestically and internationally. In order to stop the transmission of the disease workers are less available in transportation systems because restrictions across borders. These issues induce disruptions in the logistics of the food supply chains. The contemporary business environment in COVID-19 pandemic environment imposes an increased need for the development of decision-support tools. The Shadow IT solution will be described on the example of the inventory control model for frozen fruit wholesale, implemented as a spreadsheet application.

Supplier Encroachment in the Supply Chain in the E-Commerce Age: A Systematic Literature Review

The evolution of e-commerce drives suppliers to develop online direct selling channels to encroach on the retail market, in addition to the traditional distribution channels through the retailer. A systematic literature review (SLR) approach is adopted in this paper to review the existing studies using theoretical models to capture supplier encroachment behavior, as well as the related industry practice phenomena and strategic factors in the supply chain. We present the major research streams according to the selected encroachment literature from two aspects: channel conflict and coordination as well as information structures. We also generalize the significant practical strategies and strategic factors that have been investigated, combined with supplier encroachment, such as investment and spillover effects, the retailer’s store brand introduction, strategic inventory, and contract mechanism designs. More importantly, we summarize the classical theoretical models which include the basic models, the signaling game model, and the Hotelling model, and these have been widely used by scholars to capture the supplier’s encroachment behavior. Finally, we provide several suggestions which may be valuable for researchers to identify future potential research directions.