This piece aims to discuss the roles of emerging geographies within the context of global supply chains, approaching the conversation with a "systems" view, emphasizing three key facets essential to a holistic and interdisciplinary environmental analysis: -The Implications of Governmental & Economic Activities -Supply Chain Enablement Activities, Risk Mitigation in Emerging Nations -Implications Regarding Sustainability, Corporate Social Responsibility In the appreciation of the interdisciplinary implications that stem from participation in global supply networks, supply chain professionals can position their firms for continued success in the proactive construction of robust and resilient supply chains. Across industries, how will supply networks in emerging geographies continue to evolve? Appreciating the inherent nuances related to the political and economic climate of a region, the extent to which enablement activities must occur, and sustainability/CSR tie-ins will be key to acquire this understanding. This deliverable aims to leverage the work of philosophers, researchers and business personnel as these questions are explored. The author will also introduce a novel method of teaching (IMRS) in the undergraduate business classroom that challenges the students to integrate their prior experiences both in the classroom and in the business world as they learn to craft locally relevant solutions to solve complex global problems.

The authors (hereinafter, "the team") engaged in a consulting project with Honeywell Process Solutions, on behalf of the New Venture Group (nVg) The New Venture Group is a student-run management consulting firm within the W.P. Carey School of Business. Its purpose is to provide an experience that allows members to learn about management consulting by interacting with real clients doing value -adding work. Through this particular client engagement, the team was asked to research and develop a structured process that would allow Honeywell Process Solutions to usefully compare 22 factories to each other on a broad range of performance issues.

This case study analyzed the internal controls of a real estate company using the widely accepted COSO framework. Testing of the internal environment and controls was completed using the COSO framework. The major internal control problem identified in the study was a lack of ethical standards in the control environment. In addition to this main problem, inadequate documentation, no separation of duties, and unqualified employees were also identified as violations of effective internal controls. The department of real estate ordered a "cease and desist" on August 8, 2013 due to illegal company activities. The company participated in illegal actions regarding: the trust account and company documentation and procedures. Material weaknesses were found in the company's internal controls; therefore the result of this study was an adverse opinion on internal controls.

The COVID-19 pandemic’s unprecedented nature caused significant disruptions in the global supply chain industry, resulting in setbacks for supply chain operations. The repercussions of the supply chain challenges impacted various industries. This thesis seeks to investigate the impact of the COVID-19 pandemic on the supply chain industry, with a focus on how disruptions have affected the efficiency and resilience of companies within this sector. Data analytics will be leveraged to analyze these disruptions and improve supply chain operations.

Cognitive technology has been at the forefront of the minds of many technology, government, and business leaders, because of its potential to completely revolutionize their fields. Furthermore, individuals in financial statement auditor roles are especially focused on the impact of cognitive technology because of its potential to eliminate many of the tedious, repetitive tasks involved in their profession. Adopting new technologies that can autonomously collect more data from a broader range of sources, turn the data into business intelligence, and even make decisions based on that data begs the question of whether human roles in accounting will be completely replaced. A partial answer: If the ramifications of past technological advances are any indicator, cognitive technology will replace some human audit operations and grow some new and higher order roles for humans. It will shift the focus of accounting professionals to more complex judgment and analysis.
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.

Amazon Prime Air is the innovative new service that promises automated drone delivery in thirty minutes or less. The platform has not yet been brought to market, but there is a plethora compelling data available that suggests it will be a unique and highly disruptive business segment for Amazon. The aim of this thesis is to analyze the framework laid out by Amazon.com, Inc. for their anticipated Prime Air drone delivery platform, and offer our recommendations for what steps the e-commerce giant should take moving forward. Following a brief recap of the company's founding and a breakdown of its various business segments, we will begin our analysis by examining past strategic decisions that Amazon has made which have directly contributed to their current market position. It is our goal to construct a narrative of what events lead the company to begin developing a fleet of automated delivery vehicles. Following this history lesson, we will review and criticize the existing elements of Amazon's Prime Air platform, and explore any possible alternatives that they could have taken to optimize the development of this exciting new technology. Criticisms will touch upon elements such as cost efficiencies, brand management, and utilization of infrastructure to name but a few. These criticisms will be based upon data sourced from Amazon's available material as well as comments from market analysts and journalists. The culminating element of our analysis will be to offer our professional recommendations as to what we believe the next logical steps that Amazon should take for their Prime Air platform. These recommendations will be informed by our criticisms and our understanding of Amazon as a corporation. This chapter will be largely concerned with guiding Amazon towards a fully optimized drone delivery platform. Our recommendations will be based upon our extensive experience concerning cost and logistical efficiencies, as well as our knowledge of Amazon as a corporation. We will offer succinct suggestions for Amazon's immediate needs as well as long-term solutions to lingering obstacles that they may face.

The purpose of this thesis is to evaluate Company F’s inventory management practices and make recommendations on how to improve ordering and reduce inventory carrying costs. With today’s software programs we are able to run analyses’ almost instantly that show us the relationship between demand and inventory. Ideally, every company wants to have enough inventory to meet customer demand, but not so much that carrying costs skyrocket. Not only does it cost more to store inventory, but it also ties up capital which is difficult to liquidate. Finding a happy medium between customer service level and carrying costs will keep company F’s franchisees satisfied and the company profitable. Using different forecast analyses’, I will be evaluating Company F’s fastest selling category of 5 products with the goal of finding the most accurate forecast model. I will also determine reorder points and reorder quantities for the rest of Company F’s SKU’s based on average usage, lead time, and safety stock. The result of my findings will provide cost savings for the company which affects the bottom line.

My recommendations to the company will be based on the findings of the analyses’ used. There may be multiple conclusions in the recommendations for demand forecasting based on each individual forecast used. However, I will give my insight on which forecast I think is more accurate and why this one would be the best to implement in terms of accuracy. Going forward, the company will be capable of implement these models and fine tune them as necessary to help streamline their inventory needs.

This thesis, through a thorough literature and content review, discusses the various ways that data analytics and supply chain management intersect. Both fields have been around for a while, but are incredibly aided by the information age we live in today. Today's ERP systems and supply chain software packages use advanced analytic techniques and algorithms to optimize every aspect of supply chain management. This includes aspects like inventory optimization, portfolio management, network design, production scheduling, fleet planning, supplier evaluation, and others. The benefit of these analytic techniques is a reduction in costs as well as an improvement in overall supply chain performance and efficiencies. The paper begins with a short historical context on business analytics and optimization then moves on to the impact and application of analytics in the supply chain today. Following that the implications of big data are explored, along with how a company might begin to take advantage of big data and what challenges a firm may face along the way. The current tools used by supply chain professionals are then discussed. There is then a section on the most up and coming technologies; the internet of things, blockchain technology, additive manufacturing (3D printing), and machine learning; and how those technologies may further enable the successful use of analytics to improve supply chain management. Companies that do take advantage of analytics in their supply chains are sure to maintain a competitive advantage over those firms that fail to do so.

Sustainable supply chain management has become increasingly more important for companies over the last decade. The need to create socially and environmentally sustainable supply chains that are also efficient and profitable is no longer something companies should do, but rather something they must do to stay competitive and successful in the long run. Through the examination of scholarly supply chain literature, case studies, and industry reports with an emphasis on digital technology, supply chain, and sustainability, a conceptual model was created to begin the research in the area of cost savings through the use of digital technologies to enable companies to be more sustainable. This paper works to define the terms sustainability, sustainable supply chain management, and intelligent supply chain designs. It focuses on the positive social and environmental impact of the implementation of leading-edge digital technologies in supply management processes by creating transparency, efficiency, and reliability throughout the supply chain. Through an applied analysis of Mattel, Rana Plaza, Nike, and Coca-Cola and a cost-benefit analysis, it is concluded that companies that implement blockchain technology into their supply management process designs may create more sustainable supply chains while increasing savings and increasing profits. Blockchain may provide the reliability and transparency needed to better manage the supply management process which will evoke better business decisions. Intelligent supply chain designs improve the environmental and social sustainability of a company while maintaining a competitive edge.

Keywords. Supply Chain Management, Social Responsibility, Sustainability, Economics, Supply Management, Blockchain, Intelligent Technology
Paper Type. Conceptual Paper

New Venture Group, a student-run consulting organization at ASU, collaborated with representatives from Intel Corporation to determine current best supplier management practices in the area of capital equipment procurement. The New Venture Group team accomplished this goal by completing the following deliverables: (1) Research and consolidate best practices for managing capital equipment suppliers. (2) Interview suppliers of capital equipment in the semiconductor industry to understand their motivators. (3) Examine top supply chain companies that utilize capital equipment manufacturers within their procurement systems. (4) Gather data and knowledge in conjunction with Intel Corporation's current practices to improve the effectiveness of the company's supplier management techniques regarding capital equipment manufacturers. The thesis report outlines the key insights and recommendations that our team extracted from the research that we performed. Our team analyzed peer-reviewed journal articles, conducted interviews with suppliers of capital equipment to semiconductor manufacturers, and surveyed buyers at top companies to reach important key insights. We then used these insights to develop the following strategies to improve Intel's capital equipment supplier management structure: All Suppliers 1. Allow high-performance suppliers to select one reward from an established portfolio of incentives. 2. Increase measurement frequency for specific metrics. 3. Use collaborative two-way measurement with a corresponding balanced scorecard. Key Suppliers of Critical Products 4. Conduct gap analysis through supplier self-assessments. 5. Implement collaborative target pricing. 6. Delegate an Ombudsman. 7. Create a value map to determine the strengths and incentivize collaboration. 8. Create comparison charts comparing supplier technological competencies versus Intel's product developments. 9. Establish a systematized product development process and strategic sourcing strategy that supports the continuation of Moore's Law.