A Hierarchical Decision Model for Ranking the Approval Criteria of Foundation of Industrial Zones in Turkey

Especially in developing countries, the use of limited public resources for infrastructure in industry, which is critical sector for the development, is a process that needs to be carefully planned. In Turkey, this planning application has been developed in producing cheap industrial parcels to potential investors in certain areas of the regions. Since Industrial Zones are so specific and narrow topic for Turkey, there is an evident need for comprehensive studies on it. Thus, this study aims creation of a hierarchical decision model (HDM) to weight the prospectives and their criteria, which are produced according to the context of a comprehensive literature search and expert panel commentary on the topic, for an optimal location of Industrial Zones in Turkey. Prospectives were determined as regional, social, industrial, zonal, economical and potential. According to the results of this model, ranking of the prospectives lined up regional and economical (same rates), industrial and potential (same rates), zonal and social. For criteria, establish the necessity to establish an industrial zone, benefits to the investor and benefits to the region are the top three criteria with rates all same

ChopStop: A Strategic Plan

This project is an analysis of the current strategies that ChopStop, a saw manufacturing company should take in the wake of the business environment today. The goal of the project is to identify the Mission, Vision and Values of the company and use these to steer the direction of the organization moving forward. This project will center on the principles and tools taught by the ETM 525 class, the text Strategic Management Competitiveness and Globalization and the tools explained between them. First, the team starts with framing the organization, its history and their milestones. We then introduce the AIM system and its importance to the ChopStop product. After a thorough competitive and product analysis, our team introduces three individual strategies which help achieve the overall goal of expanding sales and expanding the market share of the ChopStop product

Electric Scooter

In Summer 2018, The Portland Bureau of Transportation (PBOT) is conducting a four-month pilot for Shared Electric Scooters from July 23 - November 20, 2018. The current permitted companies are; Bird, Lime, and Skip. The key driver for the adoption of e-Scooters is solving the challenge regarding urban commute of an end user such as increasing traffic congestion woes and environmental concerns [1]. On the other hand, Portlanders are interested in buying e-scooter by themselves as well. Even for leasing from a firm or becoming ownership by people, an assessment becomes a need to identify best Electric Scooter brand in Portland for an effective, environmentally-friendly, and quick solution for the short distance transportation was conducted using the Hierarchical Decision Model (HDM). Hence, our study is a methodology to assess the most efficient, and affordable candidate technologies relevant to all the valid perspective and criteria. The technology candidates selected for the assessment process were Xiaomi M365 (Bird), Dockless (Skip), and Ninebot Segway (Lime). According to prospective and criteria the finding shows that Xiaomi M365 to buy (leasing by Bird) has the highest mean relative to other two E-scooter options

CatsVision: Smart Lens Marketing Plan

CatsVision is a new product Samsung is interested in developing for improved visibility in low-light conditions. The product is a set of smart contact lenses with graphene coating technology to help generate sharper image for better vision in the people diagnosed with retinitis pigmentosa. Retinitis pigmentosa is a genetic disease that leads to a breakdown and loss of cells in the retina. It is estimated to affect 1 in 3,500 to 1 in 4,000 people in the United States and Europe. This market segment is chosen to act as a launching vehicle for the product to gain acceptance information from the market as well as ramp up large scale manufacturing abilities. Retinitis pigmentosa is chosen as the primary target market segment for the introduction of the product based on best match of the consumer needs and product features. This product can then help create a path for a wide variety of new product segments. Samsung has the right mix of research, development and manufacturing processes to mass produce the product. The product is just a concept as of now and thus we are in the innovator stage of product and technology life cycle. The SWOT analysis and porter’s five forces are favorable for the product. The threat of new entrants, threat of substitution and power of buyers was evaluated to be low with the power of suppliers rated high. We believe the competitive rivalry is medium based on our analysis of the five forces. The marketing mix for the product is also described in detail in this report. The product’s technical details, a rough roadmap as well as the marketable features are identified and detailed in various sections of the report. The product can be marketed to the target consumers through collaboration with the opthamologists. Eye doctors and especially ophthalmologists are identified as key partners apart from the supplier to manage for the success of the project. The go to market strategy is also presented in the report to engage the opthamologists to promote the product and reach the consumers. The report also presents the promotion, distribution and communication channels management for the success of the project. We determined that ingredient branding of the technology can help extend recognition and goodwill of the product. This would facilitate Samsung to extend the technology to consumer home entertainment segment

Constructing Winning NBA Teams Using Mixed Integer Programming

The National Basketball Association (NBA) is a professional basketball league consisting of 30 teams and up to 15 players per team. The four main methods to build team rosters are through free agency signings, trades, development league call ups and drafting new college and international players. There are existing tools for analyzing the effects of trades such as the ESPN NBA Trade Machine [1], but no widely available tools to determine optimal NBA free agent signings. An optimization model was made using R’s mixed integer linear programming package with an interactive user interface for sensitivity analysis. The user interface allows for adjustments in team salary spending and the model’s free agency pool can be adjusted to account for player signings on other teams. The model uses win shares (WS) as the key performance indicator to optimize overall team WS, which improves team efficiency (WS/team salary). WS was developed by Oliver [2] and accounts for an individual player’s offensive and defensive contributions to team wins. Quantitative measures (WS, salary, position quantity) were used for simulation in place of qualitative measures (leadership, chemistry, behavior/attitude), which are subjective values that may vary based on a team’s assessment of the player. While other models have attempted to predict a free agent’s value based on the available players over time [3], our model takes a reactionary approach,which initially outputs the optimal free agent signings for the team by position using the player’s last available salary. The offered salary can be adjusted based on a team’s valuation of each player. Since the other team’s evaluation of each player and the timing of free agents signings are unknown, a model that can quickly adapt to the fluid free agent market is more useful than a hypothetical predictive model. The results show the optimal free agent signings for each of the 17 teams under the $116M salary cap for the 2020-2021 NBA season. As expected, the model selects high efficiency (WS/salary) players, many of which are on their rookie contracts and are selected as optimal picks for multiple teams. A general manager (GM) can use the initial results to finalize the team’s evaluation of a player and adjust offered free agent salaries to see the effect on team WS and roster composition. If a free agent is signed by another team, the player can be removed from the FA pool and the model can be run again for updated optimized selections. The model is intended as a tool to optimize free agent signings. Future models can include the effects of potential draft picks on team WS. While first round draft pick salary scales are known, more analysis and modeling must be done to incorporate how amateur statistics translate to NBA impact