Alibaba: Case Analysis, Uncertainty and Managing Incentives

Introduction

Operating business in the current era where there exist fast-paced and convoluted processes, businesses are compelled to consistently acclimate their plan of action correspondingly. It has resulted from the rise of digital technology as well as information that is challenging businesses to change their ancient approaches of operating businesses. As businesses globalize their operations, interactions with clients as well as other enterprises have got to global scale. Therefore companies require improving their comprehension risks that are likely to influence the achievement of their functions, and learn contemporary approaches and techniques for effective risk management solutions. In these cases, the focus is on Alibaba Group Holding Limited on recent measures it has undertaken to manage risk and uncertainty, how it can improve, how it can minimize its negative impact on transactions, how it is dealing with moral hazards and suggested best practices, some principal-agent problems, and the tolls employed to improve its profitability and align incentives and finally on how the organization structure can be improved overall to foster profitability as well.

Discussion

About Alibaba Group Holding Limited

This organization is a Chinese-based multinational composite organization that practices exclusively on in e-commerce, internet, retail and technology. It was first founded in the year 1999 and offered business-to-business, consumer-to-consumer and business-to-consumer sales services through the internet and electronic payment services, cloud computing services and shopping searching engines researches Kim (2018). It possesses and performs a various cluster of enterprises across the globe in a number of sectors, and it is recognized by organizations like Fortune as the most adored company

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Kim (2018) further identifies that during its closing time in the year 2014, it recorded a twenty five billion US dollars of initial public offering (IPO), four years later it rose to three hundred and twenty five billion us DOLLARS while its market cap of three hundred and fifty-two billion US dollars, putting it as one of the top ten companies that are most valuable as well as the fifty-ninth largest public organization ion the globe in the Global List of 2000. In the valuation market, Alibaba became the second after Tencent Holding Limited also from China in the Asian market recording a break of five hundred billion US dollars by the end of the year 2018, and the same year became the ninth preeminent global brand value.

Recent Action against Risk and Uncertainty

Alibaba relies entirely on internet to do its business since it’s a global based organization. For that reason one of its greatest risks is management of fraud that has been the cause of trade uncertainty. Chen et al. (2015) identifies that fraud results from use of big data, which is an all-encompassing term for any collection of data set which are big, convoluted, thus leading to complexity in processing application. Large data is charismatic and invariably breeding ranging from terabytes to petabyte information. According to Bughin, Chui and Manyika (2010), this data serves a range of functions and include call center optimization, fraud risk management, intelligent traffic management, display advertising, social media analysis and several others to mention a few. With the advancement of technology, Alibaba has been able to analyze solutions on bettering their growth into the global market.

Chen et al. (2015) in his further studies discovers that large data has enabled to organization to grow exponentially for the last fourteen years where back in the year 2005, the organization was only transacting business for only ten thousand in a week and now, it handles a transaction that reaches a hundred and eighty-eight million in a day. With these growths of the business, Welsh (2014) researches that data computing, processing system and storage of data became complex requiring them to change from the data computing platform of Oracle Real Application Cluster (RAC), adapting  actual-time payment fraud prevention  mechanisms but could not avoid cases of fraud each time. Data from different sources of clients from all over the world made the risk more complex to tackle as it call for more and continuous advanced measure to facilitate safe and secure transactions.

The risk of insecure data of the buyers, sellers and manufactures that led to stealing of their personal data from the online business system t for fraud, terrorism and system hacking brought about uncertainty and it was not confined to a single country, but it was a global issue. This trade uncertainty due to insecure data was the driving factor of slow growth of the business that was expanding all over the world. A report by the Economist Intelligence Unit (EIU) identified that the index of uncertainty revolving around insecurity of data increased uncertainty by the beginning of the third quarter of the year 2018, the same time China and United States of America were increasing trade tariffs. These trade tariffs did not just end there, they extended to other countries that Alibaba was venturing in such as Mexico, Canada, European countries, Japan and several other economies as studied by Linkov et al. (2018). However, the uncertainty varied largely across income groups and regions, affecting Europe, Asian-Pacific and Western hemisphere, the global markets that Alibaba was thriving at.

How Alibaba can Improve Risk Management

Alibaba has made tremendous efforts in managing the risk of big data, bearing in mind that the advancement of technology and internet is attainable by use of mobile finance and internet, fraud was detectable to arise in various sizes and shapes. The organization developed a fraud risk monitoring and management system based on actual-time huge data processing and intelligent risk designs. The system is capable of capturing signals that depict fraud studies Lin and Lee (2012). In addition, Alibaba further advanced the system by developing a data based fraud prevention product known as the AntBuckler. Its sole purpose is to recognize all forms of malicious seemliness with flaccidity and acumen for online businesses and banks.

However, Jung et al. (2014) identifies that Alibaba has not managed to entire earn brand trust across the globe due to these risk of big data being exposed to hackers and terrorist organizations, or money transfer frauds. It I true that a well-known brand or business is all that an organization like Alibaba needed to succeed in a competitive market. But Jung et al. (2014) proposes that trust is needed to accompany since modern clients are quite different that there were in the past. Clients spend more time going through reviews before they complete a purchase, and the reason behind it is to seek trust that their data is safe when they are feeding it to the system.

Alibaba should note that clients or customers appreciate being engaged and possess connections with brands. Lin and Lee (2012) claim that in the current technological advancement and communications, there is a high level of assurance that customers’ data that ends up in the big data systems of the organization are safe, thus trust is earned. With the rise of social media, Wei and Young (2015) propose that Alibaba can outsource them to respond personally to individual clients, and by doing so, the organization would be assisting to their own mouth-to-mouth marketing and reducing risk and uncertainty altogether.

Examination of Adverse Selection Problem and Recommendation on Minimizing Negative Impact on Transaction

The rise of e-commerce has depicted the heightened significance of asymmetric information for globalization of business. In cases where there is lack of symmetric information between the buyer and the seller, or rather when one party in a deal is disadvantaged to have access to more accurate information that the other identifies Philippon and Skreta (2012). This asymmetry leads to a lack of efficiency in the price of the good or services consequently resulting to ineffective price signals. It has been identified in Alibaba Corporation when it introduced the old care market. This market has adverse issues lying around and has tremendous negative effect on the businesses. In this old car market that Alibaba had ventured into, there exist asymmetric information between the established seller and those who do care about the quality of the old car, and the seller is aware of the actual state of the car, but the buyer is in not aware of it. Ricketts (2015) claim that under the assumption that the customer cannot determine the actual quality of the vehicles being sold, the price the buyer is consenting to agree would only be the average of the quality of all used or old vehicles on a feasibility-weighted basis, and would only be consenting to pay the price relying on the normal, but in actual manner the sellers with a larger than the average value would leave the market with only a low quality. Therefore, the end result is that old vehicles are being sold but high quality vehicles are not.

The reasons for the adverse selection according to Sandler (2012) of the second hand vehicles are the varying information or data acquired by the various parties involved in the market. These are the seller, Alibaba Corporation, but the buyer possesses less or no information at all. This asymmetric information was one of the major causes of decline in the success of Alibaba in the car business, and consequently its market failed. Its continuous has hindered the trade of any other second-hand products through Alibaba website.

Therefore, Alibaba can turn around this effect by offering clients massive information, or rather powerful information-searching capabilities capable of acquiring thousands of messages in a short span of time. In addition, Linkov et al. (2018) recommends that these large quantities of messages could be harnessed to not limit information-processing aptitudes. But note that it is unlikely for a customer of constrained coherence to ease all information and verdict alternatives in the process of buying decisions in an environment that is highly networked. So, Singh Chauhan (2019) suggests that it is vital that the information reduces asymmetry of information, which promotes that both the buyer and the seller are capable of accessing enough information in regard to the vehicle business. It guarantees some absolute quality, the vehicle with description of direction and picture.

Ways in which Alibaba is dealing with Moral Hazard Problem and suggest best practices used

The growth of Alibaba depict how hybrid platforms that connect the internet platforms and retail outlets have cropped up to dominate bot the systematization as well as the payments marketplace in an environment that is digitized identifies Sapprasert and Clausen (2012). Such milestones have developed contemporary value and market with a number of new risks and opportunities. The powerful network developed by Alibaba has posed a moral hazard risk in the event that it becomes the biggest and the most connected e-retail company. With the advancement of technology, the Alibaba network imposes systemic risk in the economy, fostering moral hazard risks that have the potential the Chinese government to intervene. According to Orhan (2017), these risks involve personal data insecurity, cyber insecurity, terrorist funding, and incompliance measures that the licensed banks have to comply with and queries regarding anti-money laundering. Sheng and Soon (2016) in a study, they identify that while the organization has not been involved in any of the mentioned moral hazards, the organization has developed an exit mechanism for the stability of its business operating in large network dominating the platform.

Now that Alibaba has attained a dominant market position in China and expanded to foreign markets with its IPO in the United States of America in 2014. It has developed an impression in the financial services industries and progresses to attain its importance, therefore, Orhan (2017) suggest that the company must invest heavily in the security of the platform and its management. Most importantly Alibaba should invest in technological innovation, which is a central driving force for its operations.

Principal-Agent Problem and Evaluate the Tools it uses to align Incentives and Improve Profitability

One of the basic principal-agent problems that Alibaba faces is to hire individuals to perform tasks for it, on behalf of the founder and co-founders. It is an important necessity to hire these people since they possess skills that the founders do not possess, and those skills are vital for the success of the company. However, Simon et al. (2006) claim that the issue underlying Alibaba is that the incentives that the agents require do not align with the behavior and the best benefits of the principal. It means that the best interest of the management is not necessarily the best interests of the founder and co-founders. The founder and co-founders in this case are the principals, while the management is the agents.

So Alibaba has tried various fads in fixing these issues, but with no avail. So borrowing some strategies that some successful global institutions have employed to address the matter; such as Apple Inc., Sapprasert and Clausen (2012) identifies that it incentivized the management so as to increase the stock price, an interest to the shareholders, that let the agents benefit from the input or ideas that fosters interest and profits to the organization. In addition, Alibaba can offer cash bonuses to the agent for meeting certain targets, targets that are not too complex for the agents to achieve.

Alibaba Organizational Structure and Ways it can be changed to improve the Overall Profitability

Studies that were undertaken by Hanson et al. (2016) have asserted that organization frameworks of a company possess a significant influence towards its progress as well as the relation to its employees and the public in general. Its management is instigated by framework of command from the staff to the top management. An ideal design of structure facilitates communication, foster innovation and competition. The structure normally depends on several factors that directly or indirectly are in conjunction with the environment of the organization.

Hitt et al. (2016) outlines how Alibaba being a global based company with a large number of customers in various stores, require the organizational structure that will foster it to meet the needs of its clients, and at the same time meet the profits. Its organization structure is referred to as traditional VIE meaning traditional Variable Interest Entity. It is meant to propel to its success, by working with other ancillary organizations that oversees the market systems and the flow of goods in various parts. The company is headed by a co-founder Jack Ma, executives Ma and Xie. The management is made up of twenty-seven managers that have no shares in the organization but ensures that the interests of the shareholders are prioritized. Tan et al. (2015) further outline that it is further divided into departments and headed by departmental heads who are answerable to the manager of the branch and who makes final decisions. The departments are further divided into divisions, which are smaller sectors that aid in the achievement of more competent work. Then they are further divided into sub-sectors. Each of the managers heads a department, a division, sector or sub-sector but all have one core responsibility, that is implement the various policies that foster the organization’s operations, and attain the set goals.

The organization being global based, Kotabe and Helsen (2014) on global business management, claim that there exist trends in different markets in various branches that Alibaba has ventured into. Each branch has faced different modes of organizational structures and operations. These approaches challenges the VIE mode of organization structure, which is a horizontal system with employees answerable to the managers in their particular departments. Alibaba should therefore learn to employ various forms of organization structure that exist in different parts of the world the company has ventured into. Diefenbach and Sillince (2011), claim that these types of organization structure include functional, division and matrix organization structure that conform to the various work structures. Through this Alibaba could be able to employ local hubs of the organizations operations, where other global stores are involved, leading to a less tensed and conducive competitive advantage and foster overall profitability.

Conclusion

Alibaba is among the organizations in the current generation that has demonstrated exclusive growth and profit and interest margin when compared to other similar e-commerce companies. It relies on data that serves a range of functions and includes call center optimization, fraud risk management, intelligent traffic management, display advertising, social media analysis to manage risk and uncertainty. To minimize risk and uncertainty, Alibaba needs to offer a high level of assurance that customers’ data that ends up in the big data systems of the organization are safe, thus trust is earned by the public to continue doing business with the company. Within the Adverse Selection Problem, Alibaba encountered asymmetric information I the old car business, but all it needed to do is to offer symmetric information, or rather adequate information to its clients. On Moral Hazard issues, they originate frompersonal data insecurity, cyber insecurity, terrorist funding, and incompliance measures that the licensed banks have to comply with and queries regarding anti-money laundering. To counter these moral hazard issues Alibaba needs to and must invest heavily in the security of the platform and its management, and constant technological innovation. On Principal-Agent Problem, Alibaba has employed agents like CEOs and manager to meet the needs of the founders and co-founders. The company can incentivize the management for every successful task accomplished. Finally, the organization employs the Variable Interest Entity mode of organization structure. It is a horizontal mode of organization that has not been successful in various parts of the world. So Alibaba can employ the various types of organization structure to meet the local forms of business mode of operation therefore capable of promoting profitability.

References

• Bughin, J., Chui, M., & Manyika, J. (2010). Clouds, big data, and smart assets: Ten tech-enabled business trends to watch. McKinsey quarterly, 56(1), 75-86.
• Chen, J., Tao, Y., Wang, H., & Chen, T. (2015). Big data based fraud risk management at Alibaba. The Journal of Finance and Data Science, 1(1), 1-10.
• Diefenbach, T., & Sillince, J. A. (2011). Formal and informal hierarchy in different types of organization. Organization studies, 32(11), 1515-1537.
• Hanson, D., Hitt, M. A., Ireland, R. D., & Hoskisson, R. E. (2016). Strategic management: Competitiveness and globalisation. Cengage AU.
• Hitt, M. A., Ireland, R. D., & Hoskisson, R. E. (2016). Strategic management: Concepts and cases: Competitiveness and globalization. Cengage Learning.
• Jung, N. Y., Kim, S., & Kim, S. (2014). Influence of consumer attitude toward online brand community on revisit intention and brand trust. Journal of Retailing and Consumer Services, 21(4), 581-589.
• Kim, Y. C. (2018). Alibaba: Jack Ma’s Unique Growth Strategy and the Future of Its Global Development in the Chinese Digital Business Industry. In The Digitization of Business in China (pp. 219-247). Palgrave Macmillan, Cham.
• Kotabe, M. M., & Helsen, K. (2014). Global marketing management. Wiley Global Education.
• Lin, M. Q., & Lee, B. C. (2012). The influence of Website environment on brand loyalty: Brand trust and brand affect as mediators. International Journal of Electronic Business Management, 10(4).
• Linkov, I., Trump, B., Poinsatte-Jones, K., & Florin, M. V. (2018). Governance strategies for a sustainable digital world. Sustainability, 10(2), 440.
• Orhan, Z. H. (2017). PLS in Islamic Banking between dreams and facts: status analysis and problem solving in a case study of Turkey. In SASE Conference on Re-Constructing Collaborative and Disruptive Economy from Islamic Moral Economy Perspective, Universite Claude Bernard, Lyon (Vol. 1).
• Philippon, T., & Skreta, V. (2012). Optimal interventions in markets with adverse selection. American Economic Review, 102(1), 1-28.
• Ricketts, M. (2015). Adverse Selection, G resham's L aw and State Regulation. Economic Affairs, 35(1), 109-122.
• Sandler, R. (2012). Clunkers or junkers? Adverse selection in a vehicle retirement program. American Economic Journal: Economic Policy, 4(4), 253-81.
• Sapprasert, K., & Clausen, T. H. (2012). Organizational innovation and its effects. Industrial and Corporate Change, 21(5), 1283-1305.
• Sheng, A., & Soon, N. C. (2016). Shadow banking in China: an opportunity for financial reform. John Wiley & Sons.
• Singh Chauhan, R. (2019). Can Smart Contracts Ameliorate Adverse Selection in the Market for Second Hand Goods?. Available at SSRN 3451107.
• Simon, H., Bilstein, F. F., & Luby, F. (2006). Manage for profit, not for market share: A guide to greater profits in highly contested markets. Boston, MA: Harvard Business School Press.
• Tan, B., Pan, S. L., Lu, X., & Huang, L. (2015). The role of IS capabilities in the development of multi-sided platforms: the digital ecosystem strategy of Alibaba. com. Journal of the Association for Information Systems, 16(4), 2.
• Wei, S., & Young, A. (2015). Dual share plan in context: making sense of Hong Kong's decision not to embrace Alibaba's listing.
• Welsh, M. (2014). Resilience and responsibility: governing uncertainty in a complex world. The Geographical Journal, 180(1), 15-26.