Organizational Behavior Assigment 1 Group IV [PDF]

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Organizational Behavior Assignment #1 Case Study Analysis.

Group 4 McRando Mamengko, Inke Rentandatu, Case 1, Ethical Dilemma. There is a Drone in Your Soup Questions: 1-11. How might the R2D2 drones influence employee behavior? Do you think they will cause people to act more or less ethically? Why? 1-12. Who should get the drones initially? How can you justify your decision ethically? What restrictions for use should these people be given, and how do you think employees, both those who get drones and those who don’t, will react to this change? 1-13. How will your organization deal with sabotage or misuse of the drones? The value of an R2D2 drone is $2,500. 1-14. Many organizations already use electronic monitoring of employees, including sifting through website usage and e-mail correspondence, often without the employees’ direct knowledge. In what ways might drone monitoring be better or worse for employees than covert electronic monitoring of Web or e-mail activity? Answers: 1-11. We think it might influence employee in a bad way and they will cause people to act less ethically if there are no rules regarding the indoor drone usage. Statistically big companies tend to have less of even loose regulation regarding employee appearance, behavior, and work ethics especially big tech company like Amazon. In a company that has so many employees, it is hard to keep on track on individual if let say up to 20 % of employee is using high tech drones to fetch things indoors, now imagine 5 % of them is conducting inappropriate behavior like teasing their coworker, taking inappropriate picture or video, or even committing crime like theft or sexual harassment, it will be chaos. There must be a rule and regulation first. 1-12. we think that the one who should get the drones first is the employee whose job is delivering things or taking request from another employee, like office boy/girl, or office helper. This decision can be justified because it is helping their job, like if they want to deliver coffee, paper, or anything else they can use the drones to do it almost instantly, it will save time. The drone usage for them is restricted to work related only. Last but not least, we think the employee will act accordingly

and professionally because the drones are given to the employees to help them do their task and not be given without reason and just for recreational purpose, we think they will understand. 1-13 we will put tracking device on it that will cost additional 50$ and register each drone according to each individual employee id so that each employee responsible for their own drone and we can track it in case it goes missing. 1-14. in personal and psychological way, imagine you are doing your job and you have your boss eye in the sky watching you privately, each drone watching each individual or just one drone watching everyone it doesn’t matter, it would be nightmare, in email or website surveillance, at least you don’t know or you could ignore it, but using drones, there is no way you can not notice the drones flying by your side watching your every move. It will greatly affect your job performance.

Case Incident 1 Apple Goes Global Questions: 1-15. What are the pros and cons for local and overseas labor forces of Apple’s going global? What are the potential political implications for country relationships? 1-16. As a U.S. corporation, does Apple and its management have a moral obligation to provide jobs for U.S. employees first? If this is the case, then does this put international employees at a distinct disadvantage? 1-17. Is it possible for U.S. managers to organize, motivate, and ensure quality in their Chinese manufacturing facilities?

Answers: 1-15 The pros is obviously cheap labor forces and the large manufacturing capability of china which means apple could maximize profit by cutting the cos of production significantly, whilst the cons is the quality of the product is not as good as it made in USA, also the new apple tech advantages can be easily leak to the other Chinese manufactures. China and USA relationship is also a key factory here because we all know that the two country is not fond of each other, when the relationship goes worse it might be the end of apple operation in China. 1-16. Yes, they have, but certainly the profit margin for having a cheap labor is considerably more attractive to the Apple management. In the highly competitive and capitalistic US economy, there is no moral obligation for that. That is the harsh truth. 1-17. Yes, it is but by doing so they will eventually lost their advantages of moving their operation to China, the cheap labor. In order to organize, motivate, and ensure quality, you have to make sure your employee is well trained, and of course happy with their job, a well trained and happy

employee is a well-paid employee. We don’t think the apple management will do that in the near future.

Case Incident 2 Big Data for Dummies.

Questions 1-18. Let’s say you work in a metropolitan city for a large department store chain and your manager puts you in charge of a team to find out whether keeping the store open an hour longer each day would increase profits. What data might be available to your decision-making process? What data would be important to your decision? Questions 1-19. What kinds of data might we want in OB applications? Questions 1-20. As Braverman notes, one problem with big data is making sense of the information. How might a better understanding of psychology help you sift through all this data?

Answer 1-18 What data might be available to your decision-making process? Sales data, Transaction time of historical data, External data of Machine, Historical Pricing of the prodcust and sale data weekly and weekend. Sales and transaction data also sales in the final hours before closing versus earlier in the day? Labor costs including sales per employee used to determine additional hiring requirements versus adding hours for existing staff. Average cost per hire if workers are required for the additional store hours. If we are using a point-of-sale system, then it will generate reports for us that will help us make a wise decision. Print out our sales and transactions by hour report. This is a report that will list your total sales and the total number of transactions by hour for our business. The transactions (or number of tickets) are the more important metric. Sales can be deceiving. It may appear like we need to be open earlier, but the reality is, it may be 1 large sale that skews the data. What we want to focus on is the number of tickets (which essentially is telling us the number of customers) Study the data and consider each day individually. It may show that 8 am–9 am are busy times on the weekdays but not on the weekends. Look for patterns. It might show that business really dies off after 6 pm every day except Thursday–Saturday in this case, we would stay open later these days—but only these days.

Answer 1-19. Answers about what big data might be appropriate for OB applications could include data related to human resources, customers, and the work environment. Specific examples could include profiles of potential employees who might be recruitment candidates, employee data such as education, skills, interests, performance results, development plans, and personality profiles; customer data such as preferences about who and how they are serviced; and work environment data such as employee survey results or process data about how the workplace functions. Answer 1-20. Big data doesn’t just relate to facts it also relates to feelings and requires interpretation. Understanding how people think will help with interpretation of bigdata. Moreover, big data is often gathered so that it can be used in applications which are intended to influence people, or to help them learn which are understood from the discipline of psychology. Numbers only tell part of the story. To understand data fully, it is necessary to understand the mindset of the customer or employee. A better understanding of psychology could provide insight into the hows and whys of the data set and potentially some vision as to whether similar numbers could be expected in the future or whether they might take a different path.