The Role Of Chatbots In Business Operations To Improve Customer Interactions And Customer Satisfaction: A Case Study Of Amazon 

Griffith College Limerick

Declaration

I declare as follows:

I am declaring that this research was conducted according to my own understanding and research. I have not followed any kind of data breach and avoided all biased activities to follow the sustainable research process.

Candidate number:

Student number:

Date:

Signature:

Supervisor name:

Acknowledgement

I am grateful to my professors who have guided me throughout the research. I am also thankful to my classmates for maintaining collaborative culture in the classroom. I would also like to give special thanks to my family members for their continuous support in my research journey. Lastly, I am grateful to the almighty to giving opportunity for this research.

Abstract

The mission statement of Amazon states some of the strong goals that might benefit customers through both online and offline stores and focus on choosing comfort and pricing. According to Amazon’s mission statement, chatbots will help AWS operate better by developing insightful observations that will help improve the company’s online platform services.

At the moment, there are two types of contemporary bots that are mostly used for procurement reasons; current bots rely heavily on a basic set of data to follow standards for responding to specific needs in the procurement process. In this way, chatbots may successfully assume the role of procurement professionals in order to communicate with their AI-powered procurement software and applications. Thus, using current technology, key stakeholders in various departments may be identified, as well as their interests that have a direct impact on organisational effectiveness. Understanding the responsibilities of internal and external stakeholders is critical for meeting their interests within the context of organisational growth and development.

In this case, interpretivism was chosen to analyse the study topic using reasoning and beliefs in a social environment. The deductive strategy was used in this study to identify the phenomena in research based on existing hypotheses. The deductive research approach describes the strategy in a scientific language while also illustrating current hypotheses connected to the study issue. The mixed-method approach will be employed in this study; this research has incorporated primary quantitative and primary quantitative data gathering techniques into the action for analysing the existing elements.

Chatbot technology, which reduces the additional strain of supply chain activities in order to increase corporate performance, has an influence on the automated routine in the procurement system. Chatbots powered by Amazon Lex can therefore gain a competitive edge, improve the procurement process, and allow cost savings. As a result, as represented in the current literature, procurement and AI chatbots are determined to be compatible with one another in order to ensure the long-term success of e-commerce retailing organisations such as Amazon.

The study provides some of the key information needed to build a sustainable company concern that takes into account its reputation and its scope on a worldwide scale. The research also takes into account the efficient usage of chatbots, which may enhance the data collecting process in accordance with client demands

CHAPTER 1: INTRODUCTION

1.1. Overview

Amazon’s mission declares some of the assertive purposes that are able to benefited customers through online and offline shops and concentrate on selecting price, and comfort. Amazon’s vision statement is to improve the performance of Amazon Web Services (AWS) through the influence of chatbots that can develop influential observations to enhance the service of Amazon on the online platform. The performance of AWS is able to convert the world’s most customer-centric organisation more accessible. The strategy facilitated consumers to find and uncover anything they desire to buy online and attempt to deliver it. Hence the concern of Amazon Recognition is the benefits of creating manageable prompts to count profound learning-based policies that are significant to investigate the business invention process. The process can classify and enhance the methodological installation that can extend the applications.  Concerning the distinct business process of Amazon, it can be stated that a user can witness objects and backgrounds through the aid of AWS and chatbot. The introduction to the study offers a comprehensive analysis that may be utilised to develop a long-term research viewpoint on how to make Amazon’s business operations flexible. As a result, this dimension also goes into detail about how beneficial AWS is, how to utilise it to implement profitable, contemporary company policies, and how to do so while minimising business troubles on the internet platform. In order to emphasise Amazon’s business development criteria in accordance with its position in the global business dimension, the research also evaluates a number of technological procedures.

1.2. Purpose of the research

In this paper, the relevance of chatbots is further discussed in light of their role in improving AWS’s reputation and winning over Amazon customers. The study also focuses on addressing the chatbot’s problems in order to support its expansion in the global business sphere in accordance with Amazon’s requirement to maintain its competitive edge against its rivals in the online marketplace. The research’s primary goal is to expound on appropriate recommendations for the business performance of Amazon. Such research perspective also has the potential to strengthen and expedite AWS’s commercial position through chatbot refurbishment. Additionally, AI chatbots in particular contain a powerful business mechanism that aids in the creation of business rules that may create a strategic business process and a 60% boost in profits for e-commerce businesses (Lu et al., 2019). Chatbots cannot, however, change a customer’s preferred language. This study includes a few technological installations that recommend some of the crucial knowledge based on chatbot performance and its importance for creating strategic business variables that are currently in the current business context. Additionally, the integration of the chatbot is important for managing time within Amazon’s business performance in accordance with its requirements and expanding AWS’s business performance in the global business dimension appropriately. Regarding the complete findings section and its analysis, it is evident that the majority of participants believe that the chatbot’s functionality may enhance Amazon’s procurement strategy in accordance with the demands of the company’s online presence and future business growth.

1.3. Research rationale

Companies such as Amazon use AI chatbots not only to automate consumer support, but even help to optimise interaction rates, enhance customer affairs, and deliver practical business ideas that are able to direct revenue. In particular, AI chatbots include an effective business mechanism that is helped to generate business policies that are able to build a strategic business process and a 60% increase in earnings for e-commerce companies (Vaddadi et al., 2020). However, chatbots are incapable of adjusting customers’ preferences for language. Concerning the diverse customer base of Amazon, Amazon provides its business service around the world. Concerning the business performance of Amazon, language is one of the significant barriers that affect the business sustainability of Amazon accordingly.

The performance of Amazon chatbot faces the complications of make-up facts. This can be frustrating for the users, who would need help to obtain the data they require due to the chatbot’s absence of accuracy (Josephine, 2021). Concerning the business reputation of Amazon, the barriers to make-up facts create issues that may reduce the customer’s retting towards the AWS service and affect Amazon’s sustainable business process accordingly.

Figure 1.1: Quarterly revenue of Amazon Web Services

(Source: Statista.com, 2023)

As per the above figure, Amazon developed its business performance significantly, regarding the business growth and development of the company it can be stated that language barriers of chatbots. The data on the customer satisfaction rate of amazon has been fallen around 79% during the year of 2022 (Sadavarte and Bodanese, 2019, p. 1). Apparently, make-up facts may affect the sustainable perception of Amazon due to its lagging which makes the user frustrated. Hence the fundamental issue of Amazon in the present day through AWS is to improve the customer satisfaction rate through the effectiveness of Chabot and Enhancing the end-user background.

The research incorporate some of the significant observation that are reliable to evaluate the importance of customer loyalty and service quality according to the implementation of Chabot   (Amazon.com, 2023). The fundamental concern of the research concentrates to elaborate on proper guidelines regarding the business performance of Amazon (Davies et al., 2020, p. 209). Such research represent and accelerate the business position of AWS and improve through the renovation of the chatbot as per the customers reaction observed in the year of 2022. The entire process of this segment tries to underline the issues of language that are evaluated in this section with some effective observations as per the data accumulated from Amazon. Therefore, the barriers to make-up facts are another barrier that makes customers of Amazon frustrated during their buying process. Concerning the issues of Amazon it can be stated that the research elaborates on an effective research concern as it is evaluated in this dimension.

1.4. Aim and Objectives

Aim

The research aimed to incorporate knowledge about using chatbot benefits in enhancing procurement processes and improving the satisfaction of the stakeholders in Amazon Web Services (AWS).

Objectives

• To comprehend the vision of AWS and Amazon chatbot
• To analyse the use of Chatbots for communication with stakeholders
• To assess the use of Chatbot to maintain the stakeholder relationship in Amazon
• To elucidate the way Amazon chatbot increases company value
• To evaluate the way the Chatbot industry improves procurement functions in Amazon’s e-commerce services

Research question

RQ 1. What is the concept of AWS and Amazon chatbots?

RQ 2. What is the use of Chatbot for communication with stakeholders?

RQ 3. What is the use of Chatbot to maintain the stakeholder relationship in Amazon?

RQ 4. What is the value of a Chatbot in increasing company value?

RQ 5. How does a chatbot improve procurement functions in Amazon’s e-commerce services?

1.5. Significance

The research tries to elaborate on the importance of AWS in developing the business performance of Amazon and how it maintains a strategic business concern in relation to maintaining customer satisfaction globally. In this paper, the significance of chatbots is also elaborated according to their function in developing the perception of AWS and making it preferable to the customers of Amazon (Samuel et al., 2020, p. 104). Additionally, the research also concentrates on improving the issues of the chatbot for its future growth in the global business dimension according to the needs of the competitive advantages of Amazon following its business competitors in the online platform. The entire portion of the research’s introduction provides a thorough analysis that may be used to build a long-term research perspective on keeping Amazon’s company operations fluid. As a result, this dimension also elaborates on the usefulness of AWS and how to use it to incorporate lucrative, modern business policies and lessen business issues in the internet platform. The research also assesses several technical processes in order to highlight Amazon’s business development criteria in accordance with its position in the global business dimension.

1.6. Hypothesis

H0: AWS and chatbots have no impact on procurement functions and customer-stakeholder relationships of a company.

H1: AWS and chatbots have a significant effect on procurement functions and customer-stakeholder relationships of a company.

1.7. Structure of The Dissertation

Figure 1.2: Structure of the dissertation

(Source: Self Created)

1.8. Summary

The entire section of the introductory part of the research conveys a comprehensive analysis that is able to construct a sustainable research view in relation to maintaining the business fluency of Amazon. Therefore the effectiveness of AWS and its utilization is also elaborated in this dimension to integrate good business policies that are contemporary to reduce the business challenges in the online platform. Additionally, several types of technological mechanisms are also evaluated in this research to highlight the business development criteria of Amazon according to its position in the global business dimension. Thus the research conveys Amazon’s mission statement states some of the strong goals that can help consumers through both online and physical stores and focus on choosing comfort and pricing. According to Amazon’s mission statement, chatbots will help AWS operate better by developing insightful observations that will help improve the company’s online platform services.

CHAPTER 2: LITERATURE REVIEW

2.1 Introduction

The role of this chapter includes an empirical investigation of the research topic by critically focusing on the research objectives. In this chapter, the concept of AWS is elaborated with proper evidence and justifications in relation to procurement functions and stakeholder satisfaction. In this manner, the application of modern technologies is also explained in this chapter for developing an effective communication system among the stakeholders to improve procurement functions as well as satisfy them. Moreover, different types of modern technologies are also suggested in this chapter in order to improve procurement functions and stakeholder satisfaction at Amazon. The chatbot industry is worth $137.6 million in 2023 and it is assumed that its value would be $239.2 million by 2025. The chatbot-based interactions were assumed to double retail sales every year, from $7.3 billion in 2019 (Heber, 2023).

2.2 Concept of AWS and chatbot in improved procurement functions

One of the comprehensive and evolving cloud computing platforms called Amazon Web Service (AWS) provided by Amazon, which comprises a combination of platform-as-a-service (PaaS) which is a complete development and deployment environment in the cloud, Infrastructure-as-a-service (IaaS) which is a cloud service model that offers on-demand infrastructure resources and packaged software-as-a-service (SaaS) offerings that is an application software hosted on the cloud and used through an internet connectivity via a mobile app or web browser. According to Bandaru (2020), different tools can be offered by AWS services, for example, database storage, compute power and content delivery services. One effective AWS solution is Amazon Lex which is powered by deep learning functionalities like “natural language processing (NLU)” and “automatic speech recognition (ASR)” in order to publish bots for use around several channels. 1.70% is current market share of Amazon Lex and its current competitors are AddShoppers with 4.13%, Shogun with 20.18% and Optimizely with 70.38% market share (6sense.com, 2023). Although, in the chatbot sector, Amazon Lex has emerged in terms of a key player that significantly improves procurement, and businesses can get rid of the requirement for appointing assistants. Chatbots can drive a flawless customer experience at minimal initial costs by serving 24*7 in order to improve the procurement functions of the businesses.

In the year 2002, the first web service was launched by Amazon.com from its internal infrastructure in order to handle its online retail operations. Amazon started to offer its IaaS services in 2006 and gained popularity as the first company to introduce a cloud computing model called pay-as-you-go that allows users to store and compute at different scales as required. Different tools and solutions are offered by AWS for the software developers and enterprises that can be utilised in 190 nations with respect to data centres used by different groups like education institutions, government agencies, and non-profit and private agencies. As per Wankhede et al. (2020p.60), AWS offers services since 2007 across 87 available zones in regions across the world including multiple physical data centres which are connected with low-latency network links. Amazon Elastic Compute Cloud (EC2) offers virtual servers termed EC2 instances for improving the computing capacity, which are tailored to particular workload applications and types, for example, accelerated-computing and memory-intense jobs. In this manner, Amazon Elastic Block Store delivers block-level storage services in order to save persistent data while using EC2 instances.

According to Krishnan et al. (2022, p.195), 5% of customer service companies are using chatbots in order to improve the customer experience and mitigate latency. Many businesses adopted chatbots have emerged as winners in increasing sales and procurement opportunities by engaging and acquiring customers. Tal (2022) reported that 55% of businesses using chatbots have generated a greater volume of high-quality leads.

The functionality of chatbots is mainly influenced by scripts to carry out defined workflow without any delay, significantly enhancing the efficiency of the procurement strategies of a business. As per Samuel et al. (2020), the automation routine in the procurement system is also influenced by the chatbot technology that reduces the additional burden of supply chain operations to enhance business performance. In this manner, Amazon Lex-powered chatbots include a capacity to enhance competitive advantage in order to optimise the procurement process to enable cost savings. Key aspects of chatbot technologies in improvements of procurement functions are followed below:

Automatic speech recognition: Chatbots include a deep learning feature that helps businesses to offer an engaging user experience that allows a conversation among procurement managers and subordinates in an organisation (Choudhury and Pattnaik, 2020, p.103657). This feature of chatbots allows procurement managers to transcript text over voice messages.

Natural language understanding: in order to determine the intent of the conversation, chatbots include a unique, in-depth learning feature that helps in the improvement of procurement functions. Ray and Mathew (2020, p. 156) stated that Amazon lex power chatbots include an in-built capacity to process the data for easily and quickly understanding sophisticated and natural language bots in procurement functions. Moreover, the employees associated with the procurement functions can seamlessly communicate with each other in order to improve different functions of procurement operations.

2.3 Application of Chatbot for communication with stakeholders

In an organisation, chatbots can be used for internal and external occasions. In this manner, the employees can access the internal bots, for example, to obtain information seeking assistance with unfamiliar tasks. On the other hand, external chatbots can be used to communicate among partners or other stakeholders, for example, to support customer service. As per Lalićet al. (2020, p. 374), in corporate communications, chatbots are used in order to improve the communication system among the internal stakeholders. In this manner, the chatbots also help in gaining experience with an audience that is not critical as external stakeholders. As per Sharbaji (2021), in the context of small internal communication projects, many companies are presently testing this chatbot technology to improve internal communication systems. In this manner, chatbots allow companies to improve the availability of their services by reducing the workload of employees. It can be noted that chatbots allow staff to develop a quality communication system among internal and external stakeholders in an organisation as opined by Omarovet al. (2022, p.7143). Three most important areas in which chatbots can be useful for improving communication among the stakeholders, such as customer service, information for employees, and website personalisation.

Customer service: as per Jenneboer et al. (2022, p.39), the chatbots can seamlessly handle easy and simple questions with a standardised response to meet the expectations of the customers. In addition to that, the communication system between the customers and representatives of an organisation can be improved by the introductory response of chatbots. One of the effective features of a chatbot is to accept the enquiries of customers and answer simple questions in an immediate manner. In this manner, the complicated topics are forwarded by the chatbots to the human representatives in order to fulfil all enquiries of the customers as opined by Wubeet al. (2022, p.232). Quality customer service is one of the prime advantages of chatbots that help to improve external communication by providing answers to questions and enquiries.

Information for employees: the employees of an organisation can ask questions to chatbots instead of reading extensive FAQ documents in order to find relevant answers as well as resources for them. As per Vu et al. (2021, p. 251), the employees can use the internal chatbot system in order to gain a comprehensive understanding of the code of conduct and other organisational privacy policies. Along with that, the chatbots can also record the questions to keep a database of frequently asked questions for an improved internal knowledge database for the requirements of the employees. In this manner, the internal communication system in an organisation can be improved with the application of chatbot technology.

Content personalization: a conversation can be started by chatbots with website visitors, for instance, to gather information regarding previous knowledge and interests. In this manner, the presentation and content of the website can be adopted by chatbots to develop a better background of their needs. As per Jones and Jones (2019, p.1032), with the help of chatbots, online traffic can be engaged with communication in order to get a response from online users. The online visitors of the website can communicate with the chatbots in order to provide answers to all their enquiries and questions. The level of customer satisfaction can be increased with the help of content personalisation.

In contrast, Calvaresi et al. (2021, p. 3) stated that the chatbots also have drawbacks such as limited capabilities, which are not sophisticated enough to be of any real use. In other words, chatbots still face difficulties dealing with unexpected topics because of the high probability of mistakes. In this manner, limited transparency is another key drawback of chatbots that creates confusion in the communication process. In the context of empathy with the customers, the chatbots might not deal with the conversion process. In addition to that, limited data, limited transparency and limited expertise are critical drawbacks of chatbots that might create confusion during the conversation among the stakeholders in an organisational context. Along with that, as opined by Krishnan et al. (2022, p. 195), the internal learning process of the company can also be negatively affected because of the limited expertise of the chatbots. Moreover, chatbots need improvements in order to develop an insightful and critical communication system among the stakeholders in an organisation.

2.4 Impact of modern technologies on satisfying the stakeholders

In an organisation, the stakeholders have an important role to play and modern technologies can ensure satisfaction for all stakeholders. According to Schrettenbrunnner (2020, p.15), modern technologies have a positive effect on the business, and employees feel committed as well, as other stakeholders feel satisfied. In this manner, modern technologies, like Artificial Intelligence (AI), Machine Learning (ML), the Internet of Things (IoT), chatbots, and Cloud computing. In addition to that, modern technologies can assist in specifying the key stakeholders in an organisation. With the help of modern technology, the key stakeholders in different departments can be identified along with their interests that have a direct impact on the organisational effectiveness. It is very much important to understand the responsibility of the internal and external stakeholders in order to meet their interests within the context of organisational growth and development. Different modern technologies help to identify the key stakeholders to understand their needs and expectations.

Choudhury and Pattnaik (2020) stated that modern technologies help to develop a learning culture within an organisational culture for determining the accountabilities of stakeholders to meet their expectations. With the support of modern technologies, the interest of the stakeholders can be recognised, which additionally helps to maintain an effective learning culture in different departments in an organisation. It can be observed that modern technologies also shape the overall action plan of the internal and external stakeholders for developing an integrated communication system within the organisational culture (Licapa-Rodriguez et al., 2021, p. 1). Modern technologies also have the ability to generate high productivity in the workplace to meet the core interests of the stakeholders. In other words, the satisfaction level of the stakeholders can also be enhanced because of the involvement of modern technologies, which helps to create coordination among the internal and external stakeholders. Brunetti et al. (2020, p.697) stated that modern technologies provide an opportunity to understand the expectations and interests of the internal and external stakeholders in an organisation.

In addition to that, two types of stakeholders can be identified, for example, internal and external stakeholders. Employees are one of the significant internal stakeholders who can be satisfied by applying modern technologies, for example, chatbots (Elger and Shanaghy, 2020). With the help of chatbot technology, the employees can get detailed knowledge about the organisational code of conduct and privacy policies. It can be noted that employees can expand their knowledge about the privacy policy of the organisation by applying chatbot technology. Mogaji et al. (2020) stated that customers are other important external stakeholders in an organisation who are affected because of the implication of modern technologies, for example, chatbots, AI and machine learning.

Along with that, the enquiries and complaints of the customers can be dealt with by an application of chatbots that automatically provide simple and effective responses to satisfy the customers. Suppliers are other significant external stakeholders who can also be satisfied with an application of modern technologies, for example, IoT services. Kanakaraja (2021, p.1637) argued that GPS location tracking is one of the positive aspects of IoT as a modern technology that provides exact location-related data to suppliers. The satisfaction level of the suppliers can be achieved with the application of modern technologies like GPS tracking systems or IoT technology. In addition to that, the distributor is another significant external stakeholder who can be satisfied through the implication of modern technologies. In other words, machine learning and cloud computing are two significant modern technologies that can help to satisfy the interests of the distributors as significant external stakeholders in the organisation.

2.5 Impact of a chatbot on the improvement of procurement functions

In many procurement organisations, chatbots have been considered a reality. As per Agarwal. (2022. p.1013), bots are taking an important place in mainstream international business firms in order to deal successfully with customers. In this manner, most developers have found that chatbots play a useful role in the procurement process in order to improve different functions. In this manner, the advancement in AI has also allowed companies to develop chatbots in terms of limited skills and expertise but in the coming future, chatbots would be equipped with more conscious capabilities like the human brain and logical reasoning (Nirala et al., 2022, p.22215). At present, there are two types of modern bots mainly used for procurement purposes; current bots highly depend on a simple set of data in order to follow regulations for responding towards particular demands in the procurement process. In other words, advanced bots mainly apply natural language processing (NLP) and artificial intelligence (AI) to respond to the queries of humans. As per unvired.com, (2021), CPG Leader, a beverage manufacturing company used AI and Natural Language Processing (NLP) powered Chatbot Interface for both suppliers and employees to deliver support to address procurement queries anywhere anytime via a text interface.

On the other hand, the second type of chatbot is the most advanced and the most versatile. They enable natural language processing in order to mimic human conversational sets of patterns. Sai et al. (2022) stated that procurement and AI chatbots are compatible with each other in order to ensure sustainable growth and development through improving procurement functions. The chatbots provide support to procurement specialists by collecting vital information about inventory operations. In this manner, the chatbots can effectively play the role of procurement specialists in order to converse with their AI-powered software and application related to procurement (Anh, 2019).

Garg et al. (2021,p. 157) argued that natural language processing (NLP) and machine learning are useful for increasing the efficiency of chatbots to improve procurement functions. In this manner, chatbots also provide critical recommendations with the help of collected data related to procurement functions. On the other hand, contract management also makes sure that chatbots need to review the contracts, which is very important in terms of procurement specialists (Aarthiet al., 2020, p.6). The chatbots can extract and gather procurement-related information with the help of natural language processing (NLP) techniques by putting all information associated with a contract. In this manner, the chatbot can also compare and contrast the goals and policies of current business with procurement functions in order to improve its internal operations. Sai et al. (2022, p.1) stated that chatbots can recognise potential issues in the procurement process with the inclusion of artificial intelligence. In this manner, the chatbots can also highlight the required key information in order to analyse different entry data related to the procurement functions. The key focus of the procurement functions is associated with managerial processes for analysing the existing operations to improve the overall efficiency of the procurement process.

The development of the most advanced AI and machine learning platforms is currently a competition among technology companies as per the point of view of Samuel et al. (2020). When computers can learn and make judgments in a way that cannot be confused with their human counterparts, we will be able to use that technology to communicate with co-workers and consumers more effectively than ever before.

Chatbots can be applied in procurement to aid in bettering the judgements made regarding purchases. Because chatbots are powered by AI computers, they can evaluate all these factors and deliver a response in a matter of seconds as opined by Samuel et al. (2020). These factors include the needs identified during the chat, preferred items, preferred suppliers, contracts in place, real-time availability of products, purchasing history, context, and a variety of other variables, as opposed to a human operator who would have to inspect numerous systems and perform numerous calculations. Sai et al. (2022) stated that by doing this, the all-too-common responses like “May I call you back later about that?” would be unnecessary. The software could also incorporate the approval procedure. As per Jones and Jones (2019, p.1032), the AI may serve as the one point of communication for all phases of the purchasing process, from order confirmations to product receipts and more, thanks to the chatbot’s ability to automatically include the approved to the conversation.

The procurement sector can use chatbots in the same way that other businesses do. According to Cui et al. (2022, p.691), when customers have a question regarding a purchase or shipment, to try and get a good response, they will frequently have to spend a large amount of time on the phone and possibly be transferred from department to department. Instead of having to wait in line, simple questions can now be instantly answered thanks to chatbots. Users need only log in, input their order number, select one of the most often-asked questions, and receive their response. Also, they can get access to all relevant information, which can help them find the answer to a question they hadn’t even thought to ask yet(Desai and Ganatra, 2022, p.1). The chatbot can then interact with the consumer with a human operator to handle the situation if they are not happy with the response or have a question that is a little more peculiar. Chatbots have been taken into consideration as a reality in many procurement organisations. According to Gkinko and Elbanna (2023, p.102568), the use of chatbots is becoming increasingly vital in large, established worldwide corporate organisations in order to successfully interact with clients. In this way, the majority of developers have discovered that chatbots are effective in the procurement process for enhancing various functions. As a result, organisations have been able to create chatbots with only a limited set of skills and knowledge, but in the near future, chatbots will have more conscious capacities like the human brain and logical reasoning (Eppich et al., 2019, p.85).

Current bots heavily rely on a small collection of data in order to follow the rules and respond to specific requests in the procurement process. There are now two categories of modern bots that are primarily utilised in procurement processes. In other words, as per the view of Jenneboer et al. (2022, p.39), sophisticated bots primarily use artificial intelligence (AI) and natural language processing (NLP) to react to human questions. As per Lalić et al. (2020, p. 374), the second class of chatbots, on the other hand, are the most sophisticated and adaptable. To replicate the sets of patterns used in human communication, they enable natural language processing. According to Cui et al. (2022, p.691), by enhancing procurement functions, it is possible to achieve sustained growth and development by combining AI chatbots with procurement.

2.6 Possible ways of Chatbot technology to improve procurement functions in Amazon’s e-commerce services

Modern business operations in the competitive market are developing creative and innovative ways through the implications of modern technologies. The more creativity and technologically advanced business operations a firm has, the more client and customer base the business would have. Samuel et al. (2020, p. 104) has stated that technological implications in enhancing procurement functions is essential, and Amazon, as one of the largest technology firms in the world, has shown sustained use of technology in their operational and procurement functions. Procurement functions mainly involve the activities that are associated with obtaining goods and services which a company requires to support its day-to-day operations. As per Sharbaji (2021), the operations include sourcing, negotiating terms, purchasing items, and also conducting goods and services, along with keeping suitable records in each step of the function. According to Sadavarte and Bodanese (2019), it can be said that Amazon is constantly working on developing its technological involvement in competencies development so that they can develop exceptional operational capabilities in the market.

Chatbot is one of the essential involvements made by Amazon in their e-commerce procurement functions. As e-commerce is completely done in online digital platforms, chatbots play an important role in such services (Srivastava and Prabhakar, 2020, p. 61). Chatbot is a software application that is generally used to adequately conduct an online chat conversation through text or text-to-speech in lieu of providing direct contact with a human agent. In this context, (Davies et al. 2020, p. 209) has stated that chatbots are generally considered computer programs which are capable of maintaining a suitable conversation with a user in natural language, understanding their intent and also adequately replying based on the rules and data. According to Agarwal, (2022. p.1013), Chatbots are generally designed to convincingly simulate the way a human would typically behave as conversational partners.

Jaitly (2019, p.39) has observed that Amazon’s use of chatbots has been observed to be done through high focus as they are determined to deliver the best support services to their customers on digital platforms. Hence, they have developed their procurement functions on e-commerce platforms by implementing chatbots for delivering support to customers regarding their queries and needs. Choudhury and Pattnaik (2020) stated that Amazon uses an AWS chatbot, and with this, the customers can receive alerts and run commands to return diagnostic information effectively, invoke AWS Lambda functions and also create AWS support cases in order for the customer care team to collaborate and respond to the events and queries faster and effectively. This is mainly done so that the customers can save time and spend less time waiting on hold, and more time using the products.

Amazon’s e-commerce procurements can be highly improved and advanced with the implications of chatbots. Schrettenbrunnner (2020, p.15) has also depicted the various ways through which chatbots can be implied to improve e-commerce procurement are as follows:

• Enhancement of AI 

Chatbot is mainly AI based software that uses AI to deliver services and support to customers, hence improving chatbot services and implications wood requires detailed enhancement of AI(Wang et al., 2023, p.1). Machine learning and IoT are the major trends in the modern technology market and thus implications of these advanced AIs can adequately help the procurement of employees and customers browse, select, order practices effectively (Szpisják 2022). Not only that it also enhances the process of products and services quickly and in a more streamlined manner with higher curacy. Amazon can provide AI-powered product recommendations through using customer’s previous browsing data and searches.

• Guided buying    

Amazon can help the customers’ purchases decision-making through chatbots. Chatbots can deliver suggestions to customers based on several factors, such as needs identified while chatting, preferred suppliers, preferred items, history of purchases and real-time availability of products and services (Pakanatiet al. 2020). AI-powered computers and software can evaluate the factors and deliver responses immediately compared to a human operator that checks multiple systems and makes several calculations to provide a response. Almost 95% of customer interactions should be made through chatbots (Gonda and Chu 2019, p. 1). Amazon can record real-time interactions with e-Commerce store visitors, they can also enable potential customers to browse easily through the catalogue by developing shopping bots on the storefront.

Figure 2.1: AI-powered chatbot

(Source: Pakanatiet al. 2020)

2.7 Conceptual framework and theories

Theories play an important role in evaluating and understanding certain discussions and research. In order to effectively understand and evaluate e-commerce services and practices several theories are required to be understood. Brunetti et al. (2020, p.697) stated that for the discussions of e-commerce services and chatbot uses suitable the following theories can be implied,

• Service encounter needs theory

Service encounter needs theory (SENT) mainly defines the different mechanisms that are used in influencing outcomes for both party’s service encounter behaviors(Dang, 2022). Not only that, but this theory also suggests adverse responses from both parties are required to be studied in understanding the operations and in the services industries. The theory is developed based on the concept of service encounter, which states it is a period of time during which a consumer effectively interacts with a service (Sreeharshaet al. 2022). This is mainly defined and highlighted as a consumer’s direct contact with service providers, including face-to-face interactions and experience. Service encounters can be divided in 4 main categories that are customer, service provider, delivery systems and physical evidence.

Figure 2.2: Service encounter needs theory (SENT) theory

Source: (Szpisják, 2022)

The main factors that can have a significant impact on service encounters are a service organization, customers and contact personnel(Mishra and Pani, 2021, p.353). These factors can have significant impacts on the overall implications and evaluations of customer experience. Customer consciousness and extraversion often impacts customer service performance as stated thatMogajiet al. (2020). Hence effective management of service encounters is done through a CAS perspective. This is mainly used in managing the service encounter, this perspective embodies three important dimensions, which are engendering a service-oriented culture, influences of the emergent narratives that effectively shapes the client relationship and lastly, active monitoring of service trends and framing responses (Samuel et al. 2020).

• Theory of technology dominance

This theory mainly suggests that technology is viewed as the most effectively applied in intelligent decision aids when an experienced user is adequately paired with a sophisticated decision aid. The TTD is the complex task of credibility assessment in work examinations (Szpisják2022). The theory is implied in order to assist in credibility assessment the theory creates aids that augment the capability of the user, whether the user is a novice or professional. The use of hypotheses based on TTD is done to test the decision-making capabilities of the users as argued by Kanakaraja (2021, p.1637). In this context, it is also to be added that technology is the making, usage and knowledge of tools, machines, techniques, crafts and methods of an organization to have suitable problem-solving capabilities for performing specific functions. For example, it can be said that in the personal computer industry Apple Computers dominated after introducing Apple I in 1976. Hence it can be said that at a certain point of time a technological trajectory achieves effective dominance and this finalizes the final milestone in the dominance process (Sadavarteand Bodanese2019, p. 1).

This theory primarily proposes that technology is most successfully employed in intelligent decision aids when an experienced user is appropriately combined with a sophisticated decision aid. The TTD is the difficult duty of determining credibility in work tests. To aid in credibility evaluation, the theory develops aids that improve the capabilities of the user, whether the user is a rookie or a professional. The usage of hypotheses based on TTD is done to assess the users’ decision-making ability.

Figure 2.3: TTD theory

Source: (Jaitly, 2019)

2.8 Summary

The discussion summarized that implications of chatbots have been highly influencing for the Amazon’s overall customer support and assist services. It is observed that Amazon uses AWS and Amazon Lex chatbots in order to deliver suggestions to customers based on several factors, that mainly includes the different needs identified while chatting, preferred suppliers, preferred items, history of purchases and real-time availability of products and services.The study has included a detailed discussion and evaluation of the use of chatbots in Amazon’s procurement functions, the impacts and benefits acquired from it and how the firm is developing through the implications and evaluations of the chatbot has been discussed in the study but the research laced at multiple considerations and aspects regarding the research topic.

The research did not include the different functions and categories in which the chatbots have been implied by Amazon in order to acquire desired customer support and development. Not only has that, the different categories of stakeholders that have been considered and their requirements from the customer support services not been discussed also. The several procurements functions like services, purchases, negotiations and other have not been identified individually in order to discuss the implications and impacts of Chabot. Inclusion of these aspects would have enhanced the overall quality and depth of the research also internal and external stallholder have not been identified and evaluated separately also along with tier requirements from the Chabot services. This inclusion would enhance the overall implications and effectiveness of the study.

CHAPTER 3: RESEARCH METHODS

3.1 Introduction

This chapter gives a short introduction to the types of sampling methods used for crafting this study. Additionally, this chapter is going to depict the different steps which this research work might include for managing its sequential structure with the support of the research onion and making the findings and results more relative to the point as per the current statistics. The methods of the research might be helpful in availing the objectives along with the answers to the research questions.

3.2 Research Questions

A research question is observed to be one of the impactful statements which help a study in getting the answer to the research aim as well as research objectives in order to sequentially complete the research work. Hence, with the help of this research question development and getting their relevant answers helps in addressing the issues of the aimed topic along with addressing those with proper analysis for getting the resolving patterns disclosed (Goldschmidt and Matthews, 2022, p.101062). Additionally, the interpretation of the collected data resources is going to be evaluated and answered in the research concussion with the support of the research question. The research questions of the study are given in the following section.

1. RQ 1. What is the concept of AWS and Amazon chatbots?
2. RQ 2. What is the use of Chatbot for communication with stakeholders?
3. RQ 3. What is the use of Chatbot to maintain the stakeholder relationship in Amazon?
4. RQ 4. What is the value of a Chatbot in increasing company value?
5. RQ 5. How does a chatbot improve procurement functions in Amazon’s e-commerce services?

3.3 Research Objectives

A research objective is an intention that the researcher is willing to accomplish through the publication of this study. Henceforth, with the help of the research objectives, the main approach of this work is summarised along with helping the researcher to focus on their research aim (Zajac and Huber, 2021, p.1). These need to be developed in the initial stage of the project and need to be stated in the introduction part of the project. Therefore, the problem statements that this researcher is trying to evaluate get proper support in accordance with this given researcher’s objectives that are further related to the current perspectives. The research objectives of the study are given in the following section.

• To comprehend the vision of AWS and Amazon chatbot
• To analyse the use of Chatbots for communication with stakeholders
• To assess the use of Chatbot to maintain the stakeholder relationship in Amazon
• To elucidate the way Amazon chatbot increases company value
• To evaluate the way the Chatbot industry improves procurement functions in Amazon’s e-commerce services

Research Onion:

Figure 3.1: Research onion

(Source: Saunders et al., 2015)

3.4 Research Philosophy

Research philosophy can be denoted as the set of beliefs that guide the researcher to design and execute a research study properly so that a robust conclusion can be drawn. The phrase epistemology is about the aspects that are found to be true in this philosophical sector; however, it opposes the form of doxology as it defines what is required to be true for a more systematic evolution of the research questions and the objectives (HR and Aithal, 2022, p.42). Thus, with the help of appropriate philosophical evolution, the research becomes capable of encompassing the various philosophies intended to be used in its research approach.

Positivism is a philosophical theory that is empiricist while holding all genuine knowledge of the research. These facts might not always be true or positive in the case they are able to deliver some posterior facts. On the other hand, realism philosophy depicts the point of view of being real with certain attributes about the research objectives. Thus, it incorporates the thinking of the public in an independent manner (Joshi et al., 2023, p.1648). This study is going to incorporate the interpretivism research philosophy as the reality is found in a subjective manner as per the research objectives along with availing multiple as well as social constructions. Here, interpretivism has been selected to analyze the research issue based on reasoning and beliefs in a social context. Hence, this belief in the scientific objectives with proper justification and offering the incorporation of some alternative measles in the research study is the development of new theories with the help of this study.

3.5 Research Approach

The research approach describes the procedure that is selected by the researcher to complete the selected research work. Hence, describing this approach helps the researcher to collect the datasets in their selected pattern along with analysing the datasets as per the research assumptions. Additionally, the interpreting pattern of the collected datasets is evaluated with the help of the inclusion of the appraised research approach (Young et al., 2020, p.1122). In general, this research approach is found to be segregated into two patterns that are the inductive and the descriptive approach of researcher completion.

In this study, deductive approach has been opted to identify the phenomenon in research based on existing theories. The deductive research approach states the approach which is basically in the scientific format along with depicting the existing theories related to the research topic. Thus, the researchers rely on the previous research for stating their concluding remarks on the evolution of the problem statements (Pearse, 2019, p143). On the other hand, the inductive research approach depicts the inclusion of new theories created during this research conduct that is found to be compatible with the case of the research work as it aims to deliver some newly designed models and theories on the selected topic.

3.6 Research Strategies

A research strategy might be helpful in making the overall plan of a research study along with providing enough focus on the empirical research. Thus, with the help of the provision of the experiment, grounded theory, survey, and proper action of research the research strategy becomes not only well designed but also gets the support of the proper sequential arrangement of study (Maxwell, 2021, p.111). It has been found that mainly there are two types of search strategies that one might be able to include in their reviews which are the qualitative research style and the quantitative research approach by the researchers.

Qualitative research strategy includes the perception of the nun-numerical data gathering along with analysing its connection to gain the actual picture of the reality as well as getting the attitude for motivating the current issues. On the other hand, the quantitative research strategy approaches the numerical datasets for getting the statistical measurement of the selected topic while manipulating the previously existing data by some commutation techniques the mixed methods depict the incorporation of both of these techniques into the research consideration (Cairo Notariet al.2021, p.14187). In this research, mixed-method is going to be focused; this research has included the primary quantitative and primary quantitative data collection methods into the action for evaluating the current aspects and evaluating the impact of accurate trends upgrades. Both survey and interview has been conducted in this research.

3.7 Data Collection Methods Used

A research survey is a process that might need to be conducted in order to collect real datasets from the respondents of the survey that the research is aiming to use. This collected dataset is going to be best critically analysed for getting meaningful results. Additionally, it helps in delivering the actual range of research conclusions from the crafted research questions of the study (Dong et al., 2019, p.1605). Additionally, it helps in offering the results with the current world aspect and the ultimate goal of disclosing the uncovered sights or overviews of the selected topic for the research.

This research is going to utilize the quantitative survey and qualitative interview method in order to assess the primary datasets that are collected from the business leaders and the employees of the companies. In this type of survey, the same set of question papers is going to be given to each of the participants of this survey (Roh et al., 2019, p.1328). Additionally, this is going to ask the questions to the pool via the Google form and the link with the credentials is going to be provided via the official emails of the researcher. Predetermined questions are going to help in delivering the numerical statistics that might be useful in the context of the aimed research objectives.

With the help of conducting such a research survey for organising the quantitative research study, the individual might be able to deliver higher effectiveness in their research budget as per the allocated costs for their work. Additionally, they might be seen to offer the more generalised opinions of the respondents due to which more concrete recommendations are going to be drafted for the provision of reliability and versatility in the research work (Littlejohns et al., 2020, p.2624). Hence, the cost-effectiveness along with the versatility helps in offering more impactful results and the analysis of the existing research becomes more relevant in the current era.

As per the existing observations, it has been evaluated that the inclusion of the quantitative survey has not only offered some effective advantages in the research conclusion but also has incorporated some impactful disadvantages in the work. It has been found that this type of data analysis method includes the inflexibilities in the opinion of the respondents along with the challenge regarding the actual validity of the opinions of the surveyed people (Espadotoet al., 2019,p.2153). Henceforth, easy administration of the survey often lacks encouraging accurate prediction from the respondents.

An interview method for data collection is observed to be one of the impactful discussions as well as the coding of conversations between the company hierarchies or the upper positional employees. Interview has been conducted by taking 4 managers of Amazon because interview helps to answer open ended questions in research so that research issues can be derived in board. Hence, this includes a conceivable employer along with the candidates to be participating in this session for showing their perceptions (Deterding and Waters, 2021, p.708). It is shown as a sample process which is effectively designed in order to provide help to an employer for understanding the required skills, scrutinising their employee personality along with evaluating their character traits for checking the territory learning.

It has been found that there are mainly three types of interviews that a survey might include in order to get proper evolution of the employee’s skills along with getting their perceptions for the selected context. These are structured, semi-structured as well as unstructured interview sessions. With the help of the inclusion of the semi-structured interview, a prompt discussion is going to be held between the interviewer and the interviewee in order to explore the particular themes (Eppichet al., 2019). On the other hand, the unstructured interview is a sudden interview session organised without any previous planning by the non-directive interviewing sessions. However, the structured interview is chosen in this context as it helps in assessing the predesigned questions along with offering a standardised set of questions for the selected topic as per the current era and market trends.

With the help of the inclusion of the structured interview, the interviewers are capable of delivering reliable results to the assessors along with delivering the results without any external training requirements from the assessors. Additionally, this helps in offering the understanding level in a more examined manner; however, a powerful form of assessment is going to be observed via this structure of interview conduction (Low, 2019, p.123). Hence, without any additional training conduction, the results might be able to provide some additional details to the study that might be helpful in evaluating the consequences as per the current context and perceptions of the selected respondents.

Due to the inclusion of the structured interview, one might be able to develop the question sets previously, however, it often turns out to be complex ones in later research. On the other hand, structured interviews often lack proper test communications to the research. Furthermore, intense processes are also found to be scarce in quantity with limited scopes for future usage (Jyothiet al., 2020, p.122048). Thus, the requirements of the experts are found to be one of the key issues in organising the structured interviews in this study.

3.7. a The Sampling Process

The overall population for which information is requested is referred to as the target population. Ideally, this ought to concern the vulnerable population. The population for which a sample is selected is referred to as the study population (Stratton, 2021, p.373). Generally, the target and research populations ought to be the same.

In this research work, for interview,the4 managers of Amazon are going to be interviewed in order to get their perceptions about the current issues that are rising due to the inclusion of technological tools like chatbots. They are going to provide the raw data for identifying the possible methods that are going to be helpful in managing the procurement policies of developed companies (Campbell et al., 2020, p.652). Open ended questions have been asked to the participants in interview.

In this case of survey, the selected population is going to be near about 250 people from the developed companies. However, only 55 participants from the population size have been selected as the sample size of the survey. Close ended questions are asked to participants in survey.

3.7.a.1 Sampling frame

A frame of reference for sampling in analytics is the point of origin material or equipment from which a model is obtained. It is a checklist of all persons within a people who may be tested, which may comprise people, households, or associations. Thus, the frame of reference for selection is the index on which the sampling units are illustrated (Ames et al., 2019, p.1). The list strength sometimes be a listing of divisions, such as a phone text from which phone digits will be tested, or it might be some additional narrative of the inhabitants, such as a map from which rooms will be tested.

3.7.a.2 Sample size

The sample size in statistics is the number of distinct samples utilised in an experiment. For instance, when we are conducting research on 55 persons who watch television in a particular town, the participant pool size is 55 (Lakens, 2022, p.33267). It is also known as Sample Statistics. In this case, the sample size is going to be 55 participants for survey. On the other hand, the number of participants for interview is 4 managers of Amazon.

3.8 Conclusion

With the help of this chapter, the accurate concept of the interpretivism research approach along with the inductive research design is gained. Additionally, it has depicted the population size along with the same size of the survey and the interviews. Thus, with the help of crafting this chapter decoratively, proper planning for making the study might be overviewed by the readers.

CHAPTER 4: FINDINGS AND DISCUSSION

4.1 Chapter introduction

All four responders in the interview are discovered to have little knowledge of the chatbot, despite the fact that the use of this technical tool is critical for managing the renown of the e-commerce industry, which is developing daily with a large consumer base internationally. However, successful utilisation must be supervised by corporate specialists in order for the firm to expand properly while also incorporating a suitable variety of customer acquisitions, according to the views of the second and third interview respondents.Through this chapter contradictions along with similarities are going to be evaluated about the role of chatbot operations in improvising customer interactions. In this section, the survey questions and interview transcript are developed for assessing the results of the research. It might also help in assessing customer satisfaction with the usage of AWS by Amazon while surveying their customers and interviewing managers of the company from different business sections.

4.2 Findings analysis and discussion

Theme 1: Demographic analysis of the survey and interview respondents

Figure 4.1: Gender of the respondents

(Source: Self-created)

As per the above-given graph, it has been observed that the majority of the respondents are in the female sexual genre, nearly about 61.8% which implies that the company is helping in creating a better world for women while empowering their financial status as they become employed in a notable company.Thus, the rest of the survey respondents which is nearly about 36.4% are found to be belonging to the gender segment of male. The inclusion of such diversity defines that the company is willing to show equality in its employee engagement process.

Figure 4.2: Age of the respondents

(Source: Self-created)

Considering the above graph, it has been found that most of the respondents to this survey belong to the age group of young adults in which from 20 years up to 30 years employees are taken into consideration nearly about a percentile of 50.9%. Thus, the inclusion of advanced technologies is known to the majority of people belonging to this age group. It has been found that diversity in the age segment of the employees as well as the customers might be found for the company as they are willing to gain both experience and new innovations together. 49.1% of the respondents are beyond the age limit of 30 years due to which the company are able to provide higher stability with the experience and perceptions.

Figure 4.3: Engagement period of the respondents

(Source: Self-created)

As per the above-shown graph, most of the respondents in this survey are found to be newcomers in this field and are newly employed staff about an amount of 40%. Thus, it can be depicted that the company do not try to retain the employees for a long period to maintain their diversity.

The interview conducted with the four managers of Amazon from their different business operation genres. The majority of the participants are within the age group of 22 years to 32 years which is recognised as the young adult age segment. Hence, it can be depicted that the company is trying to employ the youth who are eager to imply advanced technologies in their business operations while managing their consequences. The interviewed managers are chosen randomly although they have a minimum experience of 1 year and one of the majors is found to be skilful enough for managing his employment in this daily evolving entity for nearly 5 years as stated by the fourth respondent of this interview session. The chosen interviewed managers are chosen randomly to avoid any image of gender discrimination and selected two males along with two female managers from the company. This depicts that the company is eager to provide equal chances to everyone and tries to avoid any discriminatory mindsets in its business operations.

All four respondents in the interview are found to have a minimal idea about the chatbot as the usage of this technical tool is very important for managing the fame of the e-commerce sector as it is evolving daily with a vast customer base globally. However, effective usage needs to be guided with the help of professionals of the company by which the company might get proper growth along with including a sufficient range of customer acquisitions as per the views of the second and the third respondent of the interview.

One of the most inclusive and dynamic cloud computing platforms is Amazon Web Service (AWS), which is offered by Amazon. It combines platform-as-a-service (PaaS), a complete environment for development and deployment in the cloud, infrastructure-as-a-service (IaaS), a cloud service model that provides on-demand infrastructure resources, and packaged software-as-a-service (SaaS) offerings, which are applications that are hosted in the cloud and used by users. As per the function of AWS services can provide a variety of tools, including database storage, computing power, and content delivery services. The majority of respondents, or about 61.8%, are classified as having a female sexual orientation based on the results of the initial analysis. This finding suggests that the company is empowering women’s financial standing as they work for a reputable company while also contributing to the improvement of the world for women. Therefore, it can be discussed that Scripts have a major impact on the operation of chatbots since they enable them to complete prescribed workflows quickly, thus boosting the effectiveness of a business’s procurement plans. The chatbot technology, which lessens the additional load of supply chain operations to improve business performance, also has an impact on the automated routine in the procurement system. In this way, chatbots powered by Amazon Lex have the ability to increase competitive advantage, optimise the procurement process, and enable cost savings.

As observed in the research paper by Wankhede et al. (2020 p.60), AWS is mainly offered to 87 available zones from the time it has been launched by the company for connecting with low-latency network links. Thus, engaging knowledge about the facts is actually visible to the company which is also supported by the survey and interviews conducted for this research work. Additionally, it also offered the noble brand view which this first web service has been able to get by Amazon.com. Hence, Amazon has been able to include this perception for managing its internal infrastructure in order to handle its online retail operations. Therefore, it can be predicted that it is also one of the most effective AWS solutions which are powered by deep learning functionalities like “natural language processing (NLU)” and “automatic speech recognition (ASR)” in order to publish bots for use around several channels (6sense.com, 2023). In order to decide the intent, chatbots contain some unique, in-depth learning feature that helps in the improvement of procurement functions as analysed from the point of view of the managers in the interview analysis. Ray and Mathew (2020, p. 156) have shown from their analysis that Amazon Lex power chatbots possess an in-built degree to analyse the data collection more easily and quickly while understanding its sophistic and unaffected language bots in procurement operations.

Figure 4.4: Idea about chatbot by the respondents

(Source: Self-created)

In the case of getting a minimal idea about the implication of advanced technological tools like chatbots, most of the employees that are 65.5% are found to get a clear idea about it. Thus, the importance of these technical tools for such e-commerce companies is found to be necessary for getting employment.

Chatbots can be used for both internal and external occasions in a business. Employees can use internal bots in this way, for example, to access information or request help with jobs they are unfamiliar with. External chatbots, on the other hand, can be used to facilitate communication between partners or other stakeholders, such as to support customer care. It has been determined that the majority of survey respondents are young adults, with a percentile of 50.9% assuming that employees between the ages of 20 and 30 are taken into consideration. Therefore, the majority of people in this age bracket are aware that advanced technology is present. About 40% of the survey participants were found to be freshly hired employees and/or new entrants into the profession. Thus, it can be inferred that the corporation does not attempt to keep its workforce for an extended term in order to preserve its diversity. Chatbots enable businesses to increase the accessibility of their services by lightening the burden on staff (Choudhury and Pattnaik, 2020, p.103657). It should be highlighted that chatbots give employees the opportunity to create an effective communication system between internal and external stakeholders in an organisation. Customer service, staff information, and website personalization are the top three ways that chatbots can be effective for enhancing stakeholder communication.

As per the observations, it has been found that the managers of the company are unable to interact with their employees; however, they are trying to include advanced technological tools for communicating with their employees regularly. It might help them in gathering more data about innovation, market trends as well as their company flaws to make fruitful policies as stated by the first respondent of this interview session (Omarov et al., 2022, p.7143). The inclusion of this technological tool might help the company in managing its notification services and imposing higher concentration on resolving the issues for each customer segment. Additionally, it helps in offering communication services for the company with their stakeholders while managing their queries with a sufficient range of focus.

The communication with the stakeholders of the company might get improvised with the help of AWS and chatbot as per the view of the second respondent. As opined by the fourth respondent of this interview session, it helps to obtain alerts and run declarations to produce diagnostic statements, invoke lambda procedures, and create a team who might be capable of collaborating as well as responding to circumstances more quickly. Furthermore, the company might be able to indulge better search results for their customer by which they might be able to find their preferred products at the top of the list (Wube et al., 2022, p.232). Thus, past experiences might be taken into consideration as one of the major facilities for managing consumer satisfaction. The feedback of the customer might get sorted and provided proper attention by the management with the help of AWS and chatbot.

Chatbots are assessed to be capable of driving a flawless customer experience with incurring minimal initial costs by sufficing 24*7 in order to improvise the procurement functions of the businesses. The managers of the company who are assessed in the interview stated that they are usually unable to interact with their employees due to their busy schedule although they are able to connect with the employees virtually with the help of using a chatbot. Additionally, the company is willing to launch different tools and solutions offered by AWS for the software developers and enterprises that can be utilised in 190 nations with respect to data centres used by different groups like education institutions, government agencies, and non-profit and private agencies. As opined by Krishnan et al. (2022, p. 195), customer service establishments are using chatbots in order to enhance customer adventure and mitigate latency levels. Many businesses that adopted chatbots have appeared as winners in augmenting sales and procurement possibilities by engaging and accepting higher customers.

Theme 2: AWS and chatbot concept for enhanced procurement functions

Figure 4.5: Impact of AWS and Chatbot on the Procurement Function of a Company

(Source: Self-created)

As shown in the above-given figure, the usage of AWS, as well as a chatbot, is stated to be truly beneficiary by 47.3% of the respondents. Hence, the inclusion of these advanced techniques might help manage the issues raised in the procurement function of companies from such a vast genre of services.

Figure 4.6: Significance of AWS and Chatbot for the procurement function of a company

(Source: Self-created)

As per the above-given figure, the inclusion of AWS might be shown to be beneficial as it helps in delivering the contract information along with spreading the discounting conditions elaborative to the business supervisors as the majority of the respondents supports this argument for more than 45%. Additionally, it is found to offer automated inquiries to suppliers about material availability as well as suitable search by the buyers to the suppliers to know about the demands (Licapa-Rodriguez et al., 2021, p. 1).

Figure 4.7: Perception of the impact of a chatbot on procurement improvement

(Source: Self-created)

From the above-given graph, it has been found that the inclusion of a chatbot might help in improving the procurement process of the company as 30.9% of the respondents predicted that. More easy interaction might be enabled with the help of including the procurement process in the company.

Figure 4.8: Reason behind the improvements of procurement functions by chatbot

(Source: Self-created)

Through the inclusion of a chatbot, Amazon might be able to make the interaction easier and the monitoring of the consequences might be found to be easy for monitoring and enhancing their team collaborations. Inclusion of the automated operations might also help in time management and reduce overhead costs (Elger and Shanaghy, 2020).

Figure 4.9: Three top uses of chatbots in procurement for e-commerce

(Source: Self-created)

As per the opinion of the survey respondents, the three top uses of chatbots in the procurement system of e-commerce are the processing of AWS notifications easily and on time to the managers. Additionally, it helps in reducing reasons behind their dropped off by potential buyers and sending notifications to the chartrooms for comprehending customers’ queries (Niralaet al., 2022, p.22215).

Figure 4.10: Reason why the above three impacts of chatbots in procurement for e-commerce are most impactful

(Source: Self-created)

The AWS services notification helps in managing the impact of automation due to which the feature becomes more vibrant and human efficacy gets raised. Additionally, reducing reasons dropped off by potential buyers helps to manage dissatisfaction justifications for potential buyers that improve their impact (Anh, 2019). Sending notifications to the chatrooms for comprehending customers’ queries helps in managing and improving communication between chatrooms as per the opinions gained from the respondents.

The interviewer asked whether the impact of chatbot and AWS in the procurement function of the company might be beneficial or not, which each of them depicted in a positive aspect. The first respondents depicted it to be supportive for the buyers to find the most suitable suppliers with their given price and product quality. The second respondent stated that usage of AWS and chatbot in the procurement functions of the company might be beneficial as its application helps to send automatic inquiries to their material suppliers and resolves inquiries about the availability of materials. As opined by the third respondent, by relating the voice or chatbot to the system of e-procurement, the answers of the suppliers are immediately provided in the procedure and are available to all workers at all times.

On the other hand, the fourth respondent has depicted that the inclusion of a chatbot might help in knowing all contracts along with their discount concurrences and necessities and ensures that all price benefits are utilised for rankings which are truly influential for supervising the procurement process (Aarthiet al., 2020, p.69). The respondent has stated that the usage of AWS is going to help in managing the alerts of orders and provide notifications for managing the on-time deliveries to their consumers for better feedback. As per the perception of the fourth respondent, AWS might facilitate the company with better opportunities with quality of products and price ranges as it helps in sorting the best option of suppliers for the management.

As per the point of view of Samuel et al. (2020), the automation training in the procurement procedure is also assessed to be influenced by chatbot technology. It has been assessed from the survey findings that chatbot reduces the additional burden of supply chain operations in order to enhance business performance. In this manner, Samuel et al. (2020) stated that Amazon Lex-powered chatbots are able to include an additional capacity to enhance the competitive advantage of the company. Thus, the company gets accomplishments in their business operations in order to optimise the procurement process while enabling higher cost savings. Sai et al. (2022) stated that procurement and AI chatbots are compatible with each other in order to ensure sustainable growth and development through improving procurement functions. Such compliments are highly appreciated by business managers as they stated in the interview session.

On the other hand, Garg et al. (2021, p. 157) argued that natural language processing (NLP) and machine learning are useful only for increasing the efficiency of chatbots to improve procurement functions. Although the survey and the interview analysis differed from such points of view and stated the inclusion of chatbots to be beneficial in the overall growth of the company revenue. In this manner, chatbots also provide critical recommendations with the help of collected data related to procurement functions as predicted by the Amazon managers in the interview. According to Cui et al. (2022, p.691), by enhancing procurement functions, it is possible to achieve sustained growth and development while combining AI chatbots with the procurement process of the company. Thus, existing libraries along with the findings for this study depict chatbots to be truly effective in procurement management.

Theme 3: AWS and chatbot concept for enhanced relation with stakeholders

Figure 4.11: Effect of chatbot in managing the stakeholder communication

(Source: Self-created)

Considering the above graph, it has been found that chatbot helps in communicating with the stakeholders as 47.3% of the respondents support this statement. Hence, the inclusion of these technological tools might help in making in-depth relations with the company stakeholders.

Figure 4.12: Significance of chatbot in managing the stakeholder communication

(Source: Self-created)

As opined by the employees of Amazon in this survey, the inclusion of chatbots might human conversation through voice commands or chat. Additionally, it offers to embed any sort of communication mess although some differ as the user might offer limited opinions which might create less satisfied minds of stakeholders (Desai and Ganatra, 2022, p.1).

The introduction answer of chatbots can enhance the system of communication between clients and representatives of a business. One of the main benefits of chatbots is that they provide excellent customer service in addition to facilitating better external communication by responding to queries and questions. The majority of employees, or 65.5%, are found to have a clear understanding of the implications of cutting-edge technology tools like chatbots. Therefore, it can be discussed that a chatbot’s ability to handle client inquiries and provide quick answers to basic issues is one of its most useful characteristics. In order to respond to all consumer inquiries, the chatbots in this way forward the complex topics to the human agents.

Concerning the above analysis, it is discussed that the use of AWS and a chatbot, according to 47.3% of the respondents, is genuinely beneficial. Therefore, using these cutting-edge methods could assist organisations handle the problems arising from their acquisition of such a wide range of services. The majority of respondents, or more than 45%, support the claim that AWS is advantageous since it aids in sharing detailed information on discounted terms and contract delivery to business managers. Additionally, it is discovered to provide automatic enquiries to suppliers regarding material availability as well as appropriate searches by buyers to providers regarding the requests (Eppich et al., 2019, p.85). Hence the discussion relies on some of the influential functions and benefits of the best thing about chatbots is how well they serve customers and improve external communication by replying to their questions.

As per Lalićet al. (2020, p. 374), in corporate communications, chatbots are highly appreciated and used in order to improvise the communication system among internal stakeholders. In this manner, the chatbots also help in gaining experience with an audience that is not critical as external stakeholders. It has been evaluated from the survey findings that most of the respondents supported the usage of chatbots for managing communication channels with the internal as well as external stakeholders of a company. Although some of the participants are disagreeing with the point of view due to the lack of knowledge of using advanced technologies. Hence, it can be predicted that the user needs to be assisted with proper guidance and used under the supervision of experts. As per Sharbaji (2021), in the context of small internal communication projects, many companies are presently testing this chatbot technology in order to improve internal communication systems. This is also assessed from the survey and interview analysis of this research although people also confessed that guidance is highly required for managing the utilisation of the tools and techniques.

Theme 4: The impact of contemporary technology on stakeholder satisfaction

Figure 4.13: Influence of Chatbot on stakeholder satisfaction

(Source: Self-created)

As formed in the above-given graph, the inclusion of chatbots in stakeholder engagement is found to give a significant impact as per the opinion of 34.5% of respondents of this survey. Thus, the inclusion of this technology might need to be applied for managing the satisfaction level of the company stakeholders who provide financial support.

Figure 4.14: Reason behind the influence of chatbot on stakeholder satisfaction

(Source: Self-created)

The inclusion of a chatbot might help manage the time allocation to different tasks of the company along with reducing their overhead costs at a significant range. Additionally, it helps in improving staff productivity at a significant range by automating some specified procurement processes and making the employees free of their time (Srivastava and Prabhakar, 2020, p. 61).

As opined by the first respondent, chatbots help in building frequent conversions with their stakeholders which is also supported by the second respondent while adding clear descriptions about the inquiries of the business partners. Schrettenbrunnner (2020, p.15) has also depicted that modern technologies have a positive effect on the business, and employees feel committed as well, as other stakeholders feel satisfied. The third respondent stated that the inclusion of a chatbot helps in performing routine tasks while the fourth respondent stated that focusing on activity engagement might get improved and that only HR can enact it despite any machinery intervention.

Choudhury and Pattnaik (2020) stated that modern technologies help to develop a learning culture within an organisational culture for determining the accountabilities of stakeholders to meet their expectations. Thus, the inclusion of advanced technologies might help in managing in-depth relations with customers while resolving the issues faced by them. The inclusion of a chatbot might also help in managing the web traffic of the company along with its SEO sections. Moreover, procurement services might also be managed for higher SDGs achievement of the company as per the opinion of the fourth respondent. Brunetti et al. (2020, p.697) stated that modern technologies provide an opportunity to understand the expectations and interests of the internal and external stakeholders in an organisation.

The first, as well as the second respondent, has depicted that the inclusion of AWS and chatbot might help in managing the feedback and reviews on their product with prompt reaction while resolving the issues from their SEO which is very important in e-commerce programs. Mogaji et al. (2020) stated that customers are other important external stakeholders in an organisation who are affected because of the implication of modern technologies, for example, chatbots, AI and machine learning. The customers are able to interact with the suppliers along with stating their opinions for a better experience. Track purchasing patterns and consumer behaviour analysis might be monitored by this for their e-commerce programs as opined by the fourth respondent. Kanakaraja (2021, p.1637) argued that GPS location tracking is one of the positive aspects of IoT as a modern technology that provides exact location-related data to suppliers.Thus, the satisfaction level of the suppliers can be achieved with the application of modern technologies like GPS tracking systems or IoT technology.

As opined by the interviewed responses, the usage of AWS along with the performance of the chatbot needs to be monitored by an expert. Hence, with the support of modern technologies, the interest of the stakeholders can be recognised, which additionally helps to maintain an effective learning culture in different departments in an organisation. Additionally, they have provided some recommending policies for managing the guidance for using the chatbot while getting its most beneficial utility. As opined by the first respondent of the interview session, usage of the technological tools is required to be used under proper guidance from supervisors or experts. Otherwise, some significant flaws might be clearly shown by the technical tools to their customer as well as the competitors of their associated industry which in this case might be very harmful to the growth of their business (Wang et al., 2023, p.1). Additionally, the second respondent of the interview session has previewed that business models and success matrices are required in business management or lese lack of systematic structure might be found by the technical users which creates declining growth of the company.

Furthermore, theories like technological dominance as well as service encounter need might be encountered by the technical experts of the company for managing their logistics and inclusion of technical tools for supporting their growth significantly. As depicted by the third respondent of the interview session, over-dependencies are required to be avoided by the business managers along with indulging effective natural language processing (NLP) techniques that might put all the information in a selected contract (Mishra and Pani, 2021, p.353). Emotions are needed to be understood to manage the imposition of focus. Emotions are needed to be understood to manage the imposition of focus as opined by the fourth respondent of the interview session.

Theme 5: Effect of chatbot for higher consumer acquisition

Figure 4.15: Impact of Chatbot on increasing consumer engagement for better services

(Source: Self-created)

As per the opinion gained by the respondents from the survey, the chatbot helps to set triggers to react instantly to a client query or behaviour along with which it gives customers rapid one-on-one answers to naturally asked inquiries which helps in managing consumer engagement (Dang, 2022). Additionally, it helps in offering a higher engagement in transaction services as well as account management secured within a conversation window.

The introduction answer of chatbots can enhance the system of communication between clients and representatives of a business. One of the main benefits of chatbots is that they provide excellent customer service in addition to facilitating better external communication by responding to queries and questions. The majority of employees, or 65.5%, are found to have a clear understanding of the implications of cutting-edge technology tools like chatbots. Therefore, it can be discussed that a chatbot’s ability to handle client inquiries and provide quick answers to basic issues is one of its most useful characteristics. In order to respond to all consumer inquiries, the chatbots in this way forward the complex topics to the human agents.

According to Agarwal, (2022. p.1013), chatbots are taking an important place in mainstream international business firms in order to deal successfully with customers. In this manner, most developers have found that chatbots play a useful role in the procurement process in order to improve different functions due to which managers are willing to include such functions in their business process. In this manner, chatbots allow companies to improve the availability of their services by reducing the workload of employees. As per the view of Jenneboer et al. (2022, p.39), chatbots can seamlessly handle easy and simple questions with a standardised response to meet the expectations of the customers. The survey respondents also supported that the usage of chatbots helps in enhancing the communication system between the customers and representatives of an organisation through the introductory response. As per Jones and Jones (2019, p.1032), with the help of chatbots, online traffic can be engaged with communication in order to get a response from online users. The interviewed persons predicted that online visitors of the website can communicate with the chatbots in order to provide answers to all their enquiries and questions. Thus, the level of customer satisfaction can be increased with the help of content personalisation.

4.3 Summary

Research conclusions

The chatbot technology, which lessens the additional load of supply chain operations to improve business performance, also has an impact on the automated routine in the procurement system. In this way, chatbots powered by Amazon Lex have the ability to increase competitive advantage, optimise the procurement process, and enable cost savings. Hence, as depicted in the existing literature, procurement and AI chatbots are found to be compatible with each other for ensuring sustainable growth as well as development by improving procurement functions of e-commerce retailing companies like Amazon.

Strategic conclusions

It has been evaluated that Amazon might need to seamlessly handle their procurement functions along with the communication with their stakeholders with the help of using Chatbots. Additionally, the company is suggested to include the perception of their customer through in taking their feedback frequently. Using chatbots is assessed to be one of the useful acts that companies are nowadays trying to utilise for managing the queries of internal as well as external stakeholders of a company. Hence, it can be predicted that this analysis has rejected the null hypothesis of getting no impact due to the inclusion of chatbots in procurement functions. Thus, an alternative hypothesis of the research is accepted which predicted that chatbot helps in managing customer and stakeholder’s connection in a company.

Recommendations

It is highly recommended to the management of the company that they are using proper guidance for their customers and stakeholder by which the authority might be able to enact the utmost utilisation of the chatbots. AWS Lamda function is one of the best fitting technology which Amazon might need to use for managing the usage of their chatbot for procurement functions. It is also going to help in stimulating the perception of the customer of a company. Thus, through enacting appropriate AI implementation, the procurement process might be enhanced along with managing the relationship with the customer and stakeholders.

CHAPTER 5: CONCLUSION AND RECOMMENDATION

5.1. Introduction

The entire research tries to analyse some of the significant notes that are underlined following the aspect and performance of Amazon Web Service (AWS). This chapter’s purpose is to critically examine the research objectives while conducting an empirical analysis of the research issue. This chapter provides adequate evidence and reasons for the idea of AWS in connection to procurement procedures and stakeholder satisfaction. In this way, the chapter also explains how to apply contemporary technology to create an effective system of communication among the stakeholders to enhance procurement functions and satisfy them.

5.2. Linking with objectives

Linking with objective 1:To comprehend the vision of AWS and Amazon chatbot

As it is observed the first objective of the research tries to incorporate some of the influential strategies that are significant in relation to building following the criteria of AWS. Therefore, it is seen that the most comprehensive and dynamic cloud computing platform is Amazon Web Service (AWS), which is offered by Amazon. It combines platform-as-a-service (PaaS), a complete environment for development and deployment in the cloud, infrastructure-as-a-service (IaaS), a cloud service model that provides on-demand infrastructure resources, and packaged software-as-a-service (SaaS) offerings, which are applications that are hosted in the cloud and used by users. This asserts that AWS services can provide a variety of tools, including database storage, computing power, and content delivery services. More apparently the research dimension tries to analyse a proper concept following the scripts that have a major impact on the operation of chatbots since they enable them to complete prescribed workflows quickly, thus boosting the effectiveness of a business’s procurement plans.

Linking with objective 2: To analyse the use of Chatbots for communication with stakeholders

With the help of packaged software-as-a-service (SaaS) products and the infrastructure-as-a-service (IaaS) cloud service model, users may access on-demand infrastructure resources and application software over the internet by using mobile apps or web browsers.  AWS services can provide a variety of tools, including database storage, computing power, and content delivery services. In order to publish bots for usage across many channels, Amazon Lex, a powerful AWS service, uses deep learning features including “natural language processing (NLU)” and “automatic speech recognition (ASR)”. Amazon Lex now holds a market share of 1.70%; its rivals are AddShoppers, with a market share of 4.13%, Shogun, with a market share of 20.18%, and Optimizely, with a market share of 70.38%. Additionally, the research also tries to analyse some important notes Since launching its IaaS services in 2006, Amazon has acquired notoriety as the pioneer of the pay-as-you-go cloud computing model, which enables customers to store and compute at various scales as needed. AWS provides various tools and solutions for businesses and software developers that may be utilised in 190 different countries with regard to data centres used by various organisations including educational institutions, governmental organisations, non-profit organisations, and commercial agencies. AWS has been providing services since 2007 in 87 regions throughout the world, including several physical data centres that are linked by low-latency network cables.

Linking with objective 3: To assess the use of Chatbot to maintain the stakeholder relationship in Amazon

Additionally, two categories of stakeholders, such as internal and external stakeholders, can be distinguished. One of the key internal stakeholders that may be pleased by using contemporary technology, like chatbots, is the workforce. Employees may learn in-depth information about the organization’s code of conduct and privacy regulations with the use of chatbot technology. It should be highlighted that by using chatbot technology, employees may learn more about the company’s privacy policies. Contract management, on the other hand, ensures that chatbots must examine contracts, which is critical for procurement professionals. By placing all information linked with a contract, chatbots may extract and acquire procurement-related information using natural language processing (NLP) techniques. In this way, the chatbot may compare and contrast current corporate goals and policies with procurement functions in order to optimise internal processes. In this way, chatbots can emphasise the necessary vital information in order to examine various input data connected to procurement operations. The procurement functions’ primary focus is related to managerial methods for assessing existing operations in order to increase procurement efficiency.

Linking with objective 4: To elucidate the way Amazon chatbot increases company value

Chatbots may be used in the procurement industry in the same manner that other firms can. Customers who have a query about a purchase or shipment may frequently have to spend a significant amount of time on the phone and may be moved from department to department in order to receive a satisfactory response. Simple queries may now be addressed instantaneously rather than needing to wait in queue, due to chatbots. Users merely need to log in, enter their order number, and choose one of the most often-asked questions to obtain an answer. They can also have access to all pertinent information, which can help them discover a solution to a topic they hadn’t even considered asking.

Linking with objective 5:To evaluate the way the Chatbot industry improves procurement functions in Amazon’s e-commerce services

The concept of Chatbots is mostly AI-based software that employs AI to provide services and support to clients; thus, increasing chatbot services and ramifications demands extensive AI enhancement. Machine learning and IoT are key advancements in the present technological industry, and the implications of these sophisticated AIs may effectively assist employees and clients in search, choosing, and buying practices. Not only that, but it also improves the process of products and services in a more efficient and accurate manner. Therefore, it helps to improve the procurement strategies of Amazon. Amazon may deliver AI-powered product suggestions based on a customer’s prior browsing and search history.

5.3. Summary of the findings

The entire findings part of the research tries to elaborate some of the significant understandings that are able to elaborate the importance of chatbots in developing the performance of AWS in the global business dimension. Therefore, developing the interest of the stakeholders is one of the significant observations that the findings part tries to elaborate on according to the survey. Additionally, the perception of the participant employees is also accumulated in the findings part which is evaluated with proper guidelines according to the process of research findings. Certain technological installations are also encompassed in the findings part and recommend some of the important knowledge that is significant according to the performance of chatbot and its significance to building strategic business variables that are contemporary in the present business dimension accordingly. Moreover, the inclusion of the chatbot is also significant to manage time duration within the business performance of Amazon as per its needs in developing the business performance of AWS in the global business dimension accordingly. Concerning the entire findings part and its analysis it is seen that most of the participants assert that the function of chatbot can improve the procurement strategy of Amazon as per the needs of business growth of the company through its online presence. The concept of chatbot is also able to develop a strategic concern in reference to delivering some conventional aspects that can improve the interaction rate of Amazon with its customers to generate knowledge about the customers’ preferences and maintain a reliable business policy as per the needs of the customers accordingly.

5.4. A summary of the differences between the findings and the literature

As per the observation in the literature part, it is seen that an organisation such as Amazon uses chatbots to enhance internal and external operations for an occasion. In this method, the employees can improve the interior bots, for instance, to receive information desiring assistance with foreign tasks. On the other hand, the findings parts of the research underline that the influence of chatbots can improve the perception of the stakeholders and attract them for developing an investment strategy following the business reputation of Amazon in the global business dimension accordingly. Therefore, the finding part also highlights that the performance of the chatbot is also able to manage time as per the needs of business sustainability and growth. Apparently, the performance of chatbots is accentuated in both parts due to their efficiency in developing the procurement process and making a strategy that is influential for the growth of Amazon following its business reputation in the global dimension accordingly. In both the section the literature part and the findings part delivers that the effectiveness of chatbot tries to elaborate some of the significant observations that are able to build a strategic e-commerce process. Therefore, the findings part assert that the perception of chatbots is more influential to build a strategic business campaigning process according to its needs in improving the business of AWS as well.

5.5. Limitation and Contribution

The entire research of research tries to analyse some factors that are significant in relation to maintaining some objectives that may improve the research concept. Moreover, proper identification of data sources and their implementation is one of the important strategies that need to follow for this research to reduce the issues of the research. However, these factors, together with the tier needs of the Chabot services, have not been identified and assessed individually for internal and external stallholders, which would have improved the overall quality and depth of the research. The study’s overall implications and efficacy might be improved by including this.

The research delivers some of the essential knowledge that are able to construct a sustainable business concern following the reputation and its breadth in the global dimension. Additionally, the research also incorporates the effective use of chatbots that can improve the data collection process according to the customer’s needs. Therefore, the concern about time management is also developed according to improve the service quality of Amazon concerning its business reputation globally (Sreeharsha et al., 2022). Improving stakeholder engagement is another significant contribution that the research conveys according to its need to generalise the complications of investment policies and expansion of AWS to grab the competitive advantages in the global business dimension accordingly.

5.6. Suggestions for further research

Concerning the fundamental observation on the research process and the entire analysis it is seen that in the year of 2022, the business operation of Amazon are faces some complications due to the dissatisfaction of customers. As per the observation and analysis it can be stated that amazon needs to improve the performance of Chabot and delivers proper service as per the need of developing quality service and loyal customer base. Hence some part of the research convey a strategic observation that are important for the company’s future growth and mitigate the issues of business competition of AWS accordingly.

5.7. Recommendation

Recommendation for business classification

The study left out the many roles and classifications concerning such objectives it is recommended that Amazon has given chatbots in order to achieve the appropriate level of customer service and development. Additionally, the many stakeholder types that have been considered and their expectations from customer support services have not been explored. To analyse the consequences and effects of Chabot, the various procurement functions, such as services, acquisitions, negotiations, and others, have not been named individually (Gonda, and Chu, 2019). These factors, together with the tier needs of the Chabot services, have not been identified and assessed individually for internal and external stallholders, which would have improved the overall quality and depth of the research.

Better implementation strategy for Chabot

The introduction of this would increase the overall effects and efficiency of the research accordingly. The panel concluded that chatbot implications have had a significant impact on Amazon’s total customer care and assistance offerings. It has been noted that Amazon uses Amazon Lex and AWS chatbots to provide suggestions to customers based on a number of variables, primarily the various needs identified during the chat, preferred suppliers, preferred items, purchase history, and real-time availability of goods and services. The use of chatbots in Amazon’s procurement functions, the effects and advantages gained from it, and how the company is developing as a result of the implications and evaluations of the chatbot have all been covered in detail in the study. However, the research covered a wide range of considerations and aspects related to the research topic.

Content personalisation in Chabot

In current business operations, business operators are trying to personalize operational strategy as one of the key factors to improve the customer satisfaction parameter and develop the experience of business accordingly. Hence, Amazon needs to focus on personalized content that is conducted according to the personalization of the Chabot. It would help to achieve the customer satisfaction and loyalty in the operational market.  Concerning such advancement it can be recommended that Amazon needs to build a customer-focused strategy that is developed according to the reliability and needs of customers that may be improve, the brand development policy accordingly.

Innovate the GPS location tracking through Chabot

The concern of Global Positioning System, typically understood as GPS, when initially became available to civilians for better utilization of Chabot’s to improve the locational knowledge to generate simple map tools to aid drivers. Regarding the business analysis and customer segmentation process it can be seen that the performance of AWS may be developed following the business reputation of Amazon in the global dimension.

Implementing NLP in artificial intelligence of Amazon

Amazon can implement NLP (Natural Language Processing), which is a specified aspect of artificial intelligence used in the chatbots (Mathews, 2019). This would help to communicate with the customers in their own languages; so that the interaction between customers and Amazon services can be enhanced. It works through communicating with human through sound or textual methods, these types of programs are designed for supporting the customers through websites or smart phones.

5.8. Summary

Chatbot technology, which lessens the additional strain of supply chain operations to improve corporate performance, also influences the automation routine in the procurement system. In this way, chatbots powered by Amazon Lex have the ability to increase competitive advantage, improve the procurement process, and allow cost savings. In the context of TTD, technology is defined as the creation, use, and understanding of tools, machines, techniques, crafts, and processes by an organisation in order to have appropriate problem-solving capacities for fulfilling specified activities.

Reference List

1. com, (2023). Amazon Lex – market share, competitor insights in conversion optimization, 6sense Image. Available at: https://6sense.com/tech/conversion-optimization/amazon-lex-market-share (Accessed: March 28, 2023).
2. Aarthi, N.G., Keerthana, G., Pavithra, A. and Pavithra, K. (2020). Chatbot for retail shop evaluation. International Journal of Computer Science and Mobile Computing, 9(3), pp.69-77. Available at: https://www.academia.edu/download/62365388/V9I320202320200314-34937-s03wee.pdf(Accessed: March 28, 2023).
3. Agarwal, S., Agarwal, B. and Gupta, R. (2022). Chatbots and virtual assistants: a bibliometric analysis. Library Hi Tech, 40(4), pp.1013-1030. Available at: https://www.emerald.com/insight/content/doi/10.1108/LHT-09-2021-0330 (Accessed: March 28, 2023).
4. com, 2023. Today’s Deals. Accessed on: 23.5.23, Accessed from:https://www.amazon.com/
5. Ames, H., Glenton, C. and Lewin, S. (2019). Purposive sampling in a qualitative evidence synthesis: A worked example from a synthesis on parental perceptions of vaccination communication. BMC medical research methodology, 19(1), pp.1-9. Available at: https://doi.org/10.1186/s12874-019-0665-4 (Accessed: March 28, 2023).
6. Anh, T. (2019). Artificial intelligence in e-commerce: Case Amazon. Available at: https://www.theseus.fi/bitstream/handle/10024/173516/Thesis%20Tran%20Anh.pdf?sequenc(Accessed: March 28, 2023).
7. Bandaru, A.V.I.N.A.S.H. (2020). Amazon web services. Research Methods and Professional Issues, Publication, 347442916. Available at: https://www.researchgate.net/profile/Avinash-Bandaru/publication/347442916_AMAZON_WEB_SERVICES/links/5fdc33dba6fdccdcb8d6dbe0/AMAZON-WEB-SERVICES.pdf (Accessed: March 28, 2023).
8. Brunetti, F., Matt, D.T., Bonfanti, A., De Longhi, A., Pedrini, G. and Orzes, G. (2020). Digital transformation challenges: strategies emerging from a multi-stakeholder approach. The TQM Journal, 32(4), pp.697-724. Available at: https://www.emerald.com/insight/content/doi/10.1108/TQM-12-2019-0309/full/html (Accessed: March 28, 2023).
9. Cairo Notari, S., Sader, J., CaireFon, N., Sommer, J.M., Pereira Miozzari, A.C., Janjic, D., Nendaz, M. and Audétat, M.C. (2021). Understanding GPs’ clinical reasoning processes involved in managing patients suffering from multimorbidity: A systematic review of qualitative and quantitative research. International journal of clinical practice, 75(9), p.e14187. Available at: https://doi.org/10.1111/ijcp.14187 (Accessed: March 28, 2023).
10. Calvaresi, D., Ibrahim, A., Calbimonte, J.P., Schegg, R., Fragniere, E. and Schumacher, M. (2021). The evolution of chatbots in tourism: A systematic literature review. In Information and Communication Technologies in Tourism 2021: Proceedings of the ENTER 2021 eTourism Conference, January 19–22, 2021(pp. 3-16). Springer International Publishing. Available at: https://doi.org/10.1007/978-3-030-65785-7_1 (Accessed: March 28, 2023).
11. Campbell, S., Greenwood, M., Prior, S., Shearer, T., Walkem, K., Young, S., Bywaters, D. and Walker, K. (2020). Purposive sampling: complex or simple? Research case examples. Journal of research in Nursing, 25(8), pp.652-661. Available at: https://doi.org/10.1177/1744987120927206 (Accessed: March 28, 2023).
12. Choudhury, S. and Pattnaik, S. (2020). Emerging themes in e-learning: A review from the stakeholders’ perspective. Computers & Education, 144, p.103657. Available at: https://doi.org/10.1016/j.compedu.2019.103657 (Accessed: March 28, 2023).
13. Cui, R., Li, M. and Zhang, S. (2022). AI and Procurement. Manufacturing & Service Operations Management, 24(2), pp.691-706. Available at: https://doi.org/10.1287/msom.2021.0989 (Accessed: March 28, 2023).
14. Dang, D. (2022). Artificial intelligence: AI in fashion and beauty e-commerce: Zara, Sephora. Available at: https://www.theseus.fi/handle/10024/783204(Accessed: March 28, 2023).
15. Davies, J.N., Verovko, M., Verovko, O. and Solomakha, I. (2020), August. Personalization of e-learning process using ai-powered chatbot integration. In Mathematical Modeling and Simulation of Systems (MODS’2020) Selected Papers of 15th International Scientific-practical Conference, MODS, 2020 June 29–July 01, Chernihiv, Ukraine(pp. 209-216). Cham: Springer International Publishing. Available at: https://doi.org/10.1007/978-3-030-58124-4_20 (Accessed: March 28, 2023).
16. Davies, J.N., Verovko, M., Verovko, O. and Solomakha, I., 2020, August. Personalization of e-learning process using ai-powered chatbot integration. In Mathematical Modeling and Simulation of Systems (MODS’2020) Selected Papers of 15th International Scientific-practical Conference, MODS, 2020 June 29–July 01, Chernihiv, Ukraine(pp. 209-216). Cham: Springer International Publishing.https://er.chdtu.edu.ua/bitstream/ChSTU/3457/1/Springer.pdf#page=222
17. Desai, P. and Ganatra, K. (2022). Artificial Intelligence In Strengthening The Operations Of Ecommerce Based Business. 2022 Interdisciplinary Research in Technology and Management (IRTM), pp.1-7. Available at: DOI: 10.1109/IRTM54583.2022.9791598(Accessed: March 28, 2023).
18. Deterding, N.M. and Waters, M.C. (2021). Flexible coding of in-depth interviews: A twenty-first-century approach. Sociological methods & research, 50(2), pp.708-739. Available at: https://doi.org/10.1177/0049124118799377 (Accessed: March 28, 2023).
19. Dong, J., Dai, W., Liu, Y., Yu, L. and Wang, J. (2019). Forecasting Chinese stock market prices using Baidu search index with a learning-based data collection method. International Journal of Information Technology & Decision Making, 18(05), pp.1605-1629. Available at: https://doi.org/10.1142/S0219622019500287 (Accessed: March 28, 2023).
20. Elger, P. and Shanaghy, E. (2020). AI as a Service: Serverless machine learning with AWS. Manning Publications. Available at: https://books.google.com/books?hl=en&lr=&id=BeT7DwAAQBAJ&oi=fnd&pg=PR13&dq=Elger,+P.+and+Shanaghy,+E.+(2020).+AI+as+a+Service:+Serverless+machine+learning+with+AWS.+Manning+Publications.&ots=INBcCBknyU&sig=Z4GoT9cxKJY29loF2wJ9-XNe5PM(Accessed: March 28, 2023).
21. Eppich, W.J., Gormley, G.J. and Teunissen, P.W. (2019). In-depth interviews. Healthcare Simulation Research: A Practical Guide, pp.85-91. Available at: https://link.springer.com/chapter/10.1007/978-3-030-26837-4_12 (Accessed: March 28, 2023).
22. Espadoto, M., Martins, R.M., Kerren, A., Hirata, N.S. and Telea, A.C. (2019). Toward a quantitative survey of dimension reduction techniques. IEEE transactions on visualization and computer graphics, 27(3), pp.2153-2173. Available at: DOI: 10.1109/TVCG.2019.2944182 (Accessed: March 28, 2023).
23. Garg, R., Kiwelekar, A.W., Netak, L.D. and Bhate, S.S. (2021). Potential use-cases of natural language processing for a logistics organization. In Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough: Latest Trends in AI, Volume 2(pp. 157-191). Cham: Springer International Publishing. Available at: https://link.springer.com/chapter/10.1007/978-3-030-68291-0_13 (Accessed: March 28, 2023).
24. Gkinko, L. and Elbanna, A. (2023). The appropriation of conversational AI in the workplace: a taxonomy of AI chatbot users. International Journal of Information Management, 69, p.102568. Available at: https://doi.org/10.1016/j.ijinfomgt.2022.102568 (Accessed: March 28, 2023).
25. Goldschmidt, G. and Matthews, B. (2022). Formulating design research questions: A framework. Design Studies, 78, p.101062. Available at: https://mycourses.aalto.fi/pluginfile.php/1767709/course/section/220423/Goldschmidt%20%20Matthews%20%282022%29.%20Formulating%20design%20research%20questions-%20A%20framework..pdf (Accessed: March 28, 2023).
26. Gonda, D.E. and Chu, B. (2019), December. Chatbot as a learning resource? Creating conversational bots as a supplement for teaching assistant training course. In 2019 IEEE International Conference on Engineering, Technology and Education (TALE)(pp. 1-5). IEEE. Available at: https://ieeexplore.ieee.org/abstract/document/9225974/ (Accessed: March 28, 2023).
27. Heber, C. (2023). Council post: The role of chatbots in the future of the travel industry, Forbes. Forbes Magazine. Available at: https://www.forbes.com/sites/forbestechcouncil/2023/02/02/the-role-of-chatbots-in-the-future-of-the-travel-industry/?sh=6e22beb2df75 (Accessed: March 28, 2023).
28. HR, G. and Aithal, P.S. (2022). Why is it Called Doctor of Philosophy and Why Choosing Appropriate Research Philosophical Paradigm is Indispensable During Ph. D. Program in India?. International Journal of Philosophy and Languages (IJPL), 1(1), pp.42-58. Available at: https://dx.doi.org/10.2139/ssrn.4263406 (Accessed: March 28, 2023).
29. Jaitly, K. (2019). Training an AI chatbot on AWS. International Journal for Advance Research and Development, 4(4), pp.39-41. Available at: https://www.ijarnd.com/manuscript/training-an-ai-chatbot-on-aws/ (Accessed: March 28, 2023).
30. Jenneboer, L., Herrando, C. and Constantinides, E. (2022). The impact of chatbots on customer loyalty: A systematic literature review. Journal of theoretical and applied electronic commerce research, 17(1), pp.212-229. Available at: https://doi.org/10.3390/jtaer17010011 (Accessed: March 28, 2023).
31. Jones, B. and Jones, R. (2019). Public service chatbots: Automating conversation with BBC News. Digital journalism, 7(8), pp.1032-1053. Available at: https://doi.org/10.1080/21670811.2019.1609371 (Accessed: March 28, 2023).
32. Josephine, D.D., 2021. Amazon Lex based personalized chatbot for IoT LAB@ CIT. International Journal of Advance Scientific Research and Engineering Trends, 6(5).http://ijasret.com/VolumeArticles/FullTextPDF/[email protected]
33. Joshi, A., Roy, S., Manik, R.K. and Sahoo, S.K. (2023). Scientific Philosophy: Exploring Existential, Metaphysical, and Ethical Research Philosophy Behind the Question “WHO AM I?”. Journal of Pharmaceutical Negative Results, pp.1648-1671. Available at: https://www.pnrjournal.com/index.php/home/article/download/8439/11425 (Accessed: March 28, 2023).
34. Jyothi, R.K., Thenepalli, T., Ahn, J.W., Parhi, P.K., Chung, K.W. and Lee, J.Y. (2020). Review of rare earth elements recovery from secondary resources for clean energy technologies: Grand opportunities to create wealth from waste. Journal of Cleaner Production, 267, p.122048. Available at: https://www.sciencedirect.com/science/article/pii/S0959652620320953(Accessed: March 28, 2023).
35. Kanakaraja, P. (2021). IoT enabled BLE and LoRa based indoor localization without GPS. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(4), pp.1637-1651. Available at: https://turcomat.org/index.php/turkbilmat/article/view/1419 (Accessed: March 28, 2023).
36. Krishnan, C., Gupta, A., Gupta, A. and Singh, G. (2022). Impact of Artificial Intelligence-Based Chatbots on Customer Engagement and Business Growth. In Deep Learning for Social Media Data Analytics(pp. 195-210). Cham: Springer International Publishing. Available at: https://link.springer.com/chapter/10.1007/978-3-031-10869-3_11 (Accessed: March 28, 2023).
37. Lakens, D. (2022). Sample size justification. Collabra: Psychology, 8(1), p.33267. Available at: https://doi.org/10.1525/collabra.33267 (Accessed: March 28, 2023).
38. Lalić, D., Stanković, J., Gračanin, D. and Milić, B. (2020). New Technologies in Corporate Communications. In Proceedings on 25th International Joint Conference on Industrial Engineering and Operations Management–IJCIEOM: The Next Generation of Production and Service Systems 25(pp. 374-380). Springer International Publishing. Available at: https://books.google.co.in/books?hl=en&lr=&id=fC3YDwAAQBAJ&oi=fnd&pg=PR5&dq=Lali%C4%87,+D.,+Stankovi%C4%87,+J.,+Gra%C4%8Danin,+D.+and+Mili%C4%87,+B.+(2020).+New+Technologies+in+Corporate+Communications.+In+Proceedings+on+25th+International+Joint+Conference+on+Industrial+Engineering+and+Operations+Management%E2%80%93IJCIEOM:+The+Next+Generation+of+Produ&ots=q9JIczIEvl&sig=9XwcLKE3G4EbMmmKX4Id7MjiAy4&redir_esc=y#v=onepage&q&f=false (Accessed: March 28, 2023).
39. Licapa-Rodriguez, R., Gomez-Ramos, J. and Mauricio, D. (2021), October. EcoBot: Virtual assistant for e-commerce of ecological bricks based on Facebook Messenger. In 2021 IEEE Engineering International Research Conference (EIRCON)(pp. 1-4). IEEE. Available at: https://ieeexplore.ieee.org/abstract/document/9613191(Accessed: March 28, 2023).
40. Littlejohns, T.J., Holliday, J., Gibson, L.M., Garratt, S., Oesingmann, N., Alfaro-Almagro, F., Bell, J.D., Boultwood, C., Collins, R., Conroy, M.C. and Crabtree, N. (2020). The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions. Nature communications, 11(1), p.2624. Available at: https://doi.org/10.1038/s41467-020-15948-9 (Accessed: March 28, 2023).
41. Low, J. (2019). Unstructured and Semi‑structured interviews in Health Research. Researching Health: Qualitative, Quantitative and Mixed methods. London: Sage publications, pp.123-41.Available at: Available at: https://www.torrossa.com/gs/resourceProxy?an=5018523&publisher=FZ7200#page=142 (Accessed: March 28, 2023).
42. Lu, Y., Srivastava, M., Kramer, J., Kahn, A., Elfardy, H., Wang, S. and Bhardwaj, V., 2019. Goal-oriented end-to-end chatbots with profile features in a real-world setting.https://www.amazon.science/publications/goal-oriented-end-to-end-chatbots-with-profile-features-in-a-real-world-setting
43. Maxwell, J.A. (2021). Why qualitative methods are necessary for generalization. Qualitative Psychology, 8(1), p.111.Available at: https://psycnet.apa.org/record/2020-36022-001 (Accessed: March 28, 2023).
44. Mishra, A.N. and Pani, A.K. (2021). Business value appropriation roadmap for artificial intelligence. VINE Journal of Information and Knowledge Management Systems, 51(3), pp.353-368.Available at: https://www.researchgate.net/profile/Arindra-Mishra/publication/340499236_Business_value_appropriation_roadmap_for_artificial_intelligence/links/63beeebea99551743e5d7ea7/Business-value-appropriation-roadmap-for-artificial-intelligence.pdf(Accessed: March 28, 2023).
45. Mogaji, E., Soetan, T.O. and Kieu, T.A. (2020). The implications of artificial intelligence on the digital marketing of financial services to vulnerable customers. Australasian Marketing Journal, pp.j-ausmj.Available at: https://journals.sagepub.com/doi/pdf/10.1016/j.ausmj.2020.05.003 (Accessed: March 28, 2023).
46. Nirala, K.K., Singh, N.K. and Purani, V.S. (2022). A survey on providing customer and public administration-based services using AI: chatbot. Multimedia Tools and Applications, 81(16), pp.22215-22246.Available at: https://link.springer.com/article/10.1007/s11042-021-11458-y(Accessed: March 28, 2023).
47. Omarov, B., Tursynbayev, A., Zhakypbekova, G. and Beissenova, G. (2022). Effect OfChatbots In Digital Marketing To Perceive The Consumer Behaviour. Journal of Positive School Psychology, 6(8), pp.7143-7161.Available at: https://www.journalppw.com/index.php/jpsp/article/download/11040/7128(Accessed: March 28, 2023).
48. Pakanati, D., Thanner, G. and Reddy, R.R. (2020). Design of College Chatbot using Amazon Web Services.Available at: https://ijsret.com/wp-content/uploads/2020/11/IJSRET_V6_issue6_743.pdf (Accessed: March 28, 2023).
49. Pearse, N. (2019). An illustration of a deductive pattern matching procedure in qualitative leadership research. Electronic Journal of Business Research Methods, 17(3), pp143-154.Available at: https://academic-publishing.org/index.php/ejbrm/article/download/1398/1361 (Accessed: March 28, 2023).
50. Ray, A. and Mathew, R. (2020). Review of Cloud-Based Natural Language Processing Services and Tools for Chatbots. In Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI-2018)(pp. 156-162). Springer International Publishing.Available at: https://link.springer.com/chapter/10.1007/978-3-030-24643-3_18 (Accessed: March 28, 2023).
51. Roh, Y., Heo, G. and Whang, S.E. (2019). A survey on data collection for machine learning: a big data-ai integration perspective. IEEE Transactions on Knowledge and Data Engineering, 33(4), pp.1328-1347.Available at: https://arxiv.org/pdf/1811.03402 (Accessed: March 28, 2023).
52. Sadavarte, S.S. and Bodanese, E. (2019), December. Pregnancy companion chatbot using alexa and amazon web services. In 2019 IEEE Pune Section International Conference (PuneCon)(pp. 1-5). IEEE.Available at: https://www.researchgate.net/profile/Sanket-Sadavarte/publication/341835909_Pregnancy_Companion_Chatbot_Using_Alexa_and_Amazon_Web_Services/links/612efbd80360302a006f6e30/Pregnancy-Companion-Chatbot-Using-Alexa-and-Amazon-Web-Services.pdf (Accessed: March 28, 2023).
53. Sadavarte, S.S. and Bodanese, E., 2019, December. Pregnancy companion chatbot using alexa and amazon web services. In 2019 IEEE Pune Section International Conference (PuneCon)(pp. 1-5). IEEE.https://www.researchgate.net/profile/Sanket-Sadavarte/publication/341835909_Pregnancy_Companion_Chatbot_Using_Alexa_and_Amazon_Web_Services/links/612efbd80360302a006f6e30/Pregnancy-Companion-Chatbot-Using-Alexa-and-Amazon-Web-Services.pdf
54. Sai, B., Thanigaivelu, S., Shivaani, N., Babu, S. and Ramaa, A. (2022), December. Integration of Chatbots in the Procurement Stage of a Supply Chain. In 2022 6th International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)(pp. 1-5). IEEE.Available at: https://ieeexplore.ieee.org/abstract/document/10026367/ (Accessed: March 28, 2023).
55. Samuel, I., Ogunkeye, F.A., Olajube, A. and Awelewa, A. (2020), November. Development of a voice chatbot for payment using amazon lex service with eyowo as the payment platform. In 2020 International Conference on Decision Aid Sciences and Application (DASA)(pp. 104-108). IEEE.Available at: https://www.researchgate.net/profile/Ayobami-Olajube/publication/348531152_Development_of_a_Voice_Chatbot_for_Payment_Using_Amazon_Lex_Service_with_Eyowo_as_the_Payment_Platform/links/600b1a7da6fdccdcb872cfd7/Development-of-a-Voice-Chatbot-for-Payment-Using-Amazon-Lex-Service-with-Eyowo-as-the-Payment-Platform.pdf (Accessed: March 28, 2023).
56. Samuel, I., Ogunkeye, F.A., Olajube, A. and Awelewa, A., 2020, November. Development of a voice chatbot for payment using amazon lex service with eyowo as the payment platform. In 2020 International Conference on Decision Aid Sciences and Application (DASA)(pp. 104-108). IEEE.https://www.researchgate.net/profile/Ayobami-Olajube/publication/348531152_Development_of_a_Voice_Chatbot_for_Payment_Using_Amazon_Lex_Service_with_Eyowo_as_the_Payment_Platform/links/600b1a7da6fdccdcb872cfd7/Development-of-a-Voice-Chatbot-for-Payment-Using-Amazon-Lex-Service-with-Eyowo-as-the-Payment-Platform.pdf
57. Saunders, M.N., Lewis, P., Thornhill, A. and Bristow, A. (2015). Understanding research philosophy and approaches to theory development.Available at: http://oro.open.ac.uk/53393/ (Accessed: March 28, 2023).
58. Schrettenbrunnner, M.B. (2020). Artificial-intelligence-driven management. IEEE Engineering Management Review, 48(2), pp.15-19.Available at: https://ieeexplore.ieee.org/abstract/document/9079641/ (Accessed: March 28, 2023).
59. Sreeharsha, A.S.S.K., Kesapragada, S.M. and Chalamalasetty, S.P. (2022). Building Chatbot Using Amazon Lex and Integrating with A Chat Application. International Journal of Scientific Research in Engineering and Management (IJSREM), 6(04).Available at: https://www.researchgate.net/profile/Sai-Kesapragada/publication/359704268_Building_Chatbot_Using_Amazon_Lex_and_Integrating_with_A_Chat_Application/links/6249971b21077329f2eec0cb/Building-Chatbot-Using-Amazon-Lex-and-Integrating-with-A-Chat-Application.pdf (Accessed: March 28, 2023).
60. Sreeharsha, A.S.S.K., Kesapragada, S.M. and Chalamalasetty, S.P., 2022. Building Chatbot Using Amazon Lex and Integrating with A Chat Application. International Journal of Scientific Research in Engineering and Management (IJSREM), 6(04).https://www.researchgate.net/profile/Sai-Kesapragada/publication/359704268_Building_Chatbot_Using_Amazon_Lex_and_Integrating_with_A_Chat_Application/links/6249971b21077329f2eec0cb/Building-Chatbot-Using-Amazon-Lex-and-Integrating-with-A-Chat-Application.pdf
61. Srivastava, S. and Prabhakar, T.V. (2020), September. Desirable features of a Chatbot-building platform. In 2020 IEEE International Conference on Humanized Computing and Communication with Artificial Intelligence (HCCAI)(pp. 61-64). IEEE.Available at: https://ieeexplore.ieee.org/abstract/document/9230397/(Accessed: March 28, 2023).
62. com, 2023.Quarterly revenue of Amazon Web Services from 1st quarter 2014 to 4th quarter 2022. Accessed on: 23.5.23, Accessed from:https://www.statista.com/statistics/250520/forecast-of-amazon-web-services-revenue/
63. Stratton, S.J. (2021). Population research: convenience sampling strategies. Prehospital and disaster Medicine, 36(4), pp.373-374.Available at: https://scholar.archive.org/work/l3o73olqk5heljroef5pavs2fe/access/wayback/https://www.cambridge.org/core/services/aop-cambridge-core/content/view/B0D519269C76DB5BFFBFB84ED7031267/S1049023X21000649a.pdf/div-class-title-population-research-convenience-sampling-strategies-div.pdf (Accessed: March 28, 2023).
64. Tal, S. (2022). Sales chatbots: How to grow revenue using conversational AI, CommBox. Available at: https://www.commbox.io/chatbots-sales-revenue/ (Accessed: March 28, 2023).
65. com, (2021). Procurement chatbot to support employees & suppliers at a Global Beverage Company, Unvired. Available at: https://unvired.com/case-study/a-procurement-chatbot-on-workplace-by-facebook-for-a-global-beverage-company/ (Accessed: March 28, 2023).
66. Vaddadi, S., Asri, S. and Ghemi, Y., 2020. Developing Chatbot Wrapper for Online Shopping: A Case Study of Using Generic Mobile Messaging System.https://pdfs.semanticscholar.org/a971/15288e1b4eaa028b9a9a3c7faf39697e3142.pdf
67. Vu, T.L., Tun, K.Z., Eng-Siong, C. and Banchs, R.E. (2021). Online faqchatbot for customer support. In Increasing Naturalness and Flexibility in Spoken Dialogue Interaction: 10th International Workshop on Spoken Dialogue Systems(pp. 251-259). Springer Singapore.Available at: https://link.springer.com/book/10.1007/978-981-15-9323-9 (Accessed: March 28, 2023).
68. Wang, C., Liu, Y. and Zhou, H. (2023). Consumer Consumption Behavioral Model for Business Intelligence Using Artificial Intelligence. Journal of the Knowledge Economy, pp.1-27.Available at: https://link.springer.com/article/10.1007/s13132-023-01391-w(Accessed: March 28, 2023).
69. Wankhede, P., Talati, M. and Chinchamalatpure, R. (2020). Comparative study of cloud platforms-microsoft azure, google cloud platform and amazon EC2.  Res. Eng. Appl. Sci, 5(02), pp.60-64. Available at: https://pdfs.semanticscholar.org/10bf/f6d5dee2c2dd62f85eac3ea1900045cae820.pdf (Accessed: March 28, 2023).
70. Wube, H.D., Esubalew, S.Z., Weldesellasie, F.F. and Debelee, T.G. (2022). Text-based chatbot in financial sector: A systematic literature review. Data Science in Finance and Economics, 2(3), pp.232-259.Available at: https://www.aimspress.com/aimspress-data/dsfe/2022/3/PDF/DSFE-02-03-011.pdf(Accessed: March 28, 2023).
71. Young, M., Varpio, L., Uijtdehaage, S. and Paradis, E. (2020). The spectrum of inductive and deductive research approaches using quantitative and qualitative data. Academic Medicine, 95(7), p.1122.Available at: https://journals.lww.com/academicmedicine/Fulltext/2020/07000/The_Spectrum_of_Inductive_and_Deductive_Research.41.aspx?context=FeaturedArticles&collectionId=8 (Accessed: March 28, 2023).
72. Zajac, S. and Huber, S. (2021). Objectives and methods in multi-objective routing problems: a survey and classification scheme. European Journal of Operational Research, 290(1), pp.1-25.Available at: https://www.sciencedirect.com/science/article/pii/S0377221720306160 (Accessed: March 28, 2023).

APPENDICES

Appendix 1: Survey Questionnaire

Q1: Your gender?

• Male
• Female
• Others
• Prefer not to say

Q2: Your age group?

• 20 – 29
• 30 – 39
• 40 – 49
• 50 and above

Q3: How long you are associated with Amazon?

• Less than 1 year
• 1 year – 5 years
• 5 years – 10 years
• More than 10 years

Q4: Have you heard about the concept of Chat boat?

• Yes
• No
• May be

Q5: How far do you agree with the fact that concept of AWS as well as a chatbot in order to improvise the procurement functions of a company?

• Agree
• Strongly Agree
• Disagree
• Strongly Disagree
• Neutral

Q6: Why do you think that AWS and Chatbot is needed or unnecessary to be added in the procurement functions of a company?

Q7: Chatbot is improving the business functions of procurement. Do you agree?

• Agree
• Strongly Agree
• Disagree
• Strongly Disagree
• Neutral

Q8: Why do you think that Chatbot and AWS is helpful in improving procurement business functions, if not then state your justification?

Q9: In your opinion, what are the three top uses of chatbot technology in procurement functions in the e-Commerce usefulness of Amazon?

Q10: Why did you choose this 3?

Q11: How far do you think the idea of Chatbot in order to communicate with stakeholders is an effective way?

• Agree
• Strongly Agree
• Disagree
• Strongly Disagree
• Neutral

Q12: Why do you think that Chatbot is pivotal or unnecessary to be added to communicate with stakeholders?

Q13: Chatbots as well as other technological options are being effective for satisfying the shareholders. Do you agree?

• Agree
• Strongly Agree
• Disagree
• Strongly Disagree
• Neutral

Q14: Why do you think that Chatbot and AWS are effective or unnecessary to be added for satisfying the shareholders?

Q15: How far do you consider that integration of Chatbot is effective for increasing consumer engagement for better consumer services?

Appendix 2: Interview Transcript

1. What is your age and gender?

Ans: Respondent 1: I am 25 years old and my gender is female.

Respondent 2: I am 22 years old and my gender is male.

Respondent 3: I am 29 years old and my gender is female.

Respondent 4: I am 32 years old and my gender is male.

1. How long have you been with Amazon?

Ans: Respondent 1: I have been working in this noble organisation for near about 12 months.

Respondent 2: I have been working in this honourableorganisation for more than 15 months.

Respondent 3: I have been working in this reputed company for more than 2 years timespan.

Respondent 4: I have been working in this famous and friendly business entity for more than 5 years.

1. Do you know about AWS and chatbot application?

Ans: Respondent 1: Yes, I have some slight perception about this application although I am unable to define their exact applications elaboratively.

Respondent 2: Yes, I do have a clear idea about the application of AWS and chatbot for managing the efficacy of business operations.

Respondent 3: Yes, I am aware about the different function that can be performed via the usage of AWS and chatbot.

Respondent 4: Yes, I do have although they are very minimal in terms of its proficiency enactment.

1. Can AWS and chatbot be applied in the functions of Amazon?

Ans: Respondent 1: Yes, they can be used for managing the notification services for the Amazon company.

Respondent 2: The AWS and chatbot can be used for managing the communication services for the Amazon company with their stakeholders.

Respondent 3: The AWS and chatbot can be used for enhancing the communication services for the Amazon company.

Respondent 4: It helps to receive alerts and run commands to return diagnostic information, invoke lambda functions, and create team who can collaborate and respond to events faster.

1. Do you think that it might be helpful to improvise the procurement functions of a company?

Ans: Respondent 1: Yes, the implications might be beneficial as voice and chatbots support buyers in their search for suitable suppliers, products and prices.

Respondent 2: Usage of AWS and chatbot in the procurement functions of the company might be beneficial as its application helps to send automated inquiries to suppliers and thus inquire about the availability of materials and products.

Respondent 3: By connecting the voice or chatbot to the e-procurement system, the supplier’s answers can be immediately fed into the system and are accessible to all employees at all times.

Respondent 4: A voice or chatbot knows all contracts plus discount agreements and conditions and can thus ensure that all price advantages are utilized for orders which is truly effective for managing the procurement process.

1. What is your perception of including AWS in Amazon for managing their procurement policies?

Ans: Respondent 1: As per my opinion, using the AWS is going to be truly effective in managing the alerts of the order so that the delivery of the products is going to reach on time.

Respondent 2: As per my point of views, using of the AWS might help the company in improvising their search results while preferring their choices in their search list on the top while analysing their past experiences.

Respondent 3: I think that the usage of AWS might help in managing the feedback solving system of the company.

Respondent 4: From my perception, using AWS might help in ensuring all price and quality advantage for the better opportunity provision of the company users.

1. What is your perception about the ways of Chatbot in order to communicate with stakeholders of Amazon?

Ans: Respondent 1: I think that the inclusion of chatbot might help the company in managing more frequent conversations with their stakeholders.

Respondent 2: From my point of views, the application of chatbot helps the stakeholders to clearly depict their inquiries while automating the business process of the company.

Respondent 3: As per the opinion of mine, the inclusion of chatbot to perform their routine tasks effectively while getting through them quickly.

Respondent 4: I think that inclusion of chatbot might help stakeholders in focusing highly on engaging their activities that are required for human capabilities which machines can not perform.

1. Do you think that the consequence of chatbots and other technological options for satisfying the shareholders might be helpful for Amazon and its growth performance?

Ans: Respondent 1: As per my opinion, inclusion of advanced technologies might help in communicating with the customers more frequently which helps in re-building in-depth relationship.

Respondent 2: From my point of views, inclusion of advanced technologies like chatbot helps in resolving the issues faced by the company shareholders due to which new innovation might be indulged in the business.

Respondent 3: I think that inclusion of advanced technologies like AWS and chatbot might help the company in managing their search engine operation for their customer which might increase the web-traffic.

Respondent 4: As per my point of view, applying the innovative technological tools like chatbot and AWS might help Amazon in managing their procurement services which direct to higher sustainable goals for the company.

1. What is your opinion of Chatbot technology to improvise procurement functions in the e-commerce usefulness of Amazon?

Ans: Respondent 1: I think using chatbot might be beneficial for the company as it helps in managing the online feedbacks and tried to enact the reaction procedures quickly.

Respondent 2: Usage of chatbot might help the company in improving their SEO operation which is very impactful in e-commerce programs.

Respondent 3: As per my opinion, using the deliver might be on time which helps in creating a noble reputation about the company.

Respondent 4: Chatbot and other technological usage might help the company in managing their track purchasing patterns and analyse consumer behaviours by monitoring user data which is very important for e-commerce programs.

1. As per your concern, state out some effective recommended policies for mitigation of the challenges by the business management.

Ans: Respondent 1: Usage of the technological tools needs guidance from supervisors or experts.

Respondent 2: Business models and success matrix are required in the business management.

Respondent 3: Over-dependencies are required to be avoided by the business managers.

Respondent 4: Emotions are needed to be understand to manage the imposition of focus.