Business Research Methodology – Assessment Answer

Introduction

A significant aspect of the growth and sustainability of any business is to continuously identify business problems and devise strategies to provide viable solutions (Bhutta et al., 2022). However, companies often encounter complex situations that require in-depth analysis to uncover the underlying issues. Therefore, thoroughly investigating a business problem is imperative to identify potential solutions (Debrah et al., 2022). Now it will determine a relevant business problem, gather relevant literature, identify the research gaps, and develop a research proposal to address the identified gap. The relevance of identifying and addressing business problems cannot be overstated in contemporary business practices.

As businesses face dynamic forces such as technological advancements, regulatory changes, and fierce competition, developing strategies to mitigate the associated risks is critical (Din et al., 2022). However, identifying these problems requires a rigorous exploration of the issue to determine the root cause. The supply chain has come under increasing pressure as globalization and digital technologies create new opportunities, challenges, and dynamic changes in market demands (Enholm et al., 2022). Companies need help to efficiently manage their supply chain, maintain customer satisfaction, and experience profitable growth. In this context emerged a Business Problem-solving case - the need for further agility and flexibility in supply chain management systems. 

Identifying the Business Problem

The first step in approaching any problem is identifying it. To identified the business problem as the need for more flexibility and agility in supply chain management (Faeq et al., 2022). Globalization, new market demands, and emerging technology have significantly changed supply chain management. Companies must continually adapt and improve their strategies to stay competitive in their business environment (Filipović, 2022). However, most companies are still using conventional supply chain management practices that need to consider the impact of external elements that affect business performance. The factors mentioned earlier cause supply chain management to be slow and inefficient, reducing responsiveness to customer demands. 

Literature Review

Formulate a comprehensive plan of research to find an adequate solution for the business problem (Gomes & Lopes, 2022). Examining and exploring past research and literature for essential insights on the subject is integral. The literature covering supply chain agility and flexibility encompasses several areas. Usually, it tackles a set of matters that generally divides into the operational or strategic procedures areas of supply chain management. Gupta & Harvey, 2022 said that the literature then illustrates different perspectives behind the need to integrate agile supply theory with today's economy's essential mindsets by relying on granularity levels and deploying accurate real-time analysis with helpful performance indicators.

The full inter-organizational slack utilization into the existing production and distribution architecture is demanded nowadays (Henriksen et al., 2022). It proposed Data analytics, scheduling, and bench-marking the distribution–organization architectural options, among others, precise specific positions to integrate improvements supported by adequate data analysis instruments applied for prompt management calculating (Hina et al., 2022). The literature shows a fulfilling need for connecting closer design-thinking-oriented internal performances of production and distribution design departments by closely linking them with the tech and IT innovation employee profiles on businesses' operational teams. 

Research Gap

Throughout researching various business cases across different industries achieving supply-chain flexibility and agility, a seamless architecture cross-challenging manufacturing-oriented distribution requirements became a very prominent aspect as the examined literature emphasized firmly addressing sophisticated data panels implementation of manufacturing resources with IT driving innovative employees profiles linking ascertaining positive improvements on sustainable magnitudes such cost-effective implementing directly incorporated into operational output without apparent inconsistencies in quality distribution (Jasim et al., 2022). The next step in developing a research proposal is to review the literature to determine the research gaps. In the literature review process, they aim to identify weaknesses, inconsistencies, and research gaps in previously conducted research on the chosen topic. They adopt an analytical and critical approach to analyzing the findings of previous works. According to Luo et al., 2022 after extensive research, they have identified that limited studies explore the need for more flexibility and agility in supply chain management and how this impacts business performance. However, the few existing studies in this area have yet to focus on developing a personalized agility model for the supply chain management. Therefore, this empirical research aims to fill this gap by creating a customized agility model for supply chain management.

Research Proposal

Further research is necessary to create a review on specific adoption models trained to facilitate analytics abstraction, revealing coded data links relationships between centralized - decentralized architectures over is reflected constant variables like goods testing methods implemented between operational nodes that help running human-supervised structures (Malodia et al., 2023). Potential solutions collected across the examined literature entail machine-learning-based suggestions for explicit challenges within rich data storage (Olaleye et al., 2022). Implemented initially on pioneering open forums within workflow restructuring enable balanced business perspectives to transparency acceptance scalability checkpoints which benefits outstanding outcomes interchange efforts that contribute growth past unsustainable deficiencies of past implementation methods ideal logistics are those very reliant upon substantial evidence. 

Developing the Research Proposal

Successful implementation of the researched findings, a thorough analysis must follow a carefully crafted proposal based on the described research gaps (Ran et al., 2022). It can follow various routes, including devising trade agreements, partnerships, geo-diverse workforce integration, and techno-augmentation for efficiency, managerial transparency, or whole series of preventative measures. Rietmeijer & Veen, 2022 discuss that organizing such key business pieces of evidence and method into the produced proposal can be helpful to allocate resources in usable form by identifying gaps reliant tools. Based on the identified research gap, to propose to conduct empirical research designed to create a personalized agility model that aims to improve the flexibility and agility of supply chain management. This research approach uses qualitative and quantitative analysis to garner the necessary data for developing the personalized model. This research offers businesses more informed decision-making processes, enabling a more flexible and responsive supply chain management strategy.

Initial Protocol Actions critical deliveries completing: 

• In the first and foremost stage, research automation evaluative implications confront part focus upon participation establishing incentivization corporations reinforcing innovation experimentation deploying solid creative activity to upgrading technology for more productions contingencies (Sefton et al., 2022). 
• Follow-up stage interactive open communication seemingly productive in analyzing pain points and undesirable gains incurred case body goals increments past methods had suffering inconvenience removing algorithm inputs for distribution architecture corrections. 
• Suggestions factoring improvements across interpretative requirements held together with constant outreach among internal organizational scopes giving proof for operative structure applications.

Overall, research proposals undertaken could make an enormous improvement over present days disjoined architecture regularly used methods for previously used by status-quo businesses ways to their distribution (Silva et al., 2023). Moreover, supply chain creating challenges in meeting satisfaction ratings across several measures, Monolithic models stifling innovation both possibilities that demanded potential inflection points effectively enabling operations for sustained interoperability combining intelligent enterprise adoption measures through the equivalent potential partnering operations variable metrics linking intelligently sophisticated workflow fabricating closing gaps between theory-based frameworks and reality approaches.

In the field of Research, a dependent variable refers to the variable that is affected or influenced by the independent variable (Tittarelli et al., 2022). The variable being studied and measured in the experiment or Research. The dependent variable is the outcome or result that is being observed and analyzed. In the theoretical model of Perceived Usefulness, the dependent variable is the perceived Usefulness of a particular technology (Tran & Kim, 2022). The degree to which a person thinks employing a particular technology would improve their performance or productivity is known as perceived Usefulness.

There are six hypotheses associated with the Perceived Usefulness model. The first hypothesis states that perceived Usefulness positively correlates with an individual's intention to use the technology (Bhutta et al., 2022). The second hypothesis posits that perceived ease of use positively influences perceived Usefulness. The third hypothesis states that social influence positively affects perceived Usefulness. The fourth hypothesis in the model suggests that facilitating conditions influence perceived Usefulness (Debrah et al., 2022). The fifth hypothesis proposes that lifestyle compatibility positively affects perceived Usefulness. Finally, the sixth hypothesis posits that perceived trust positively correlates with perceived Usefulness.

Mediating variables refer to variables between the independent and dependent variables in the theoretical model (Din et al., 2022). The mediating variable for Perceived Usefulness is the attitude toward using technology. Attitude towards using technology mediates the relationship between perceived Usefulness and intention to use. The intensity or direction of the relationship between the independent and dependent variables is influenced by moderating variables (Enholm et al., 2022). In the Perceived Usefulness model, the moderating variable is the computer self-efficacy of the user. Computer self-efficacy moderates the relationship between perceived Usefulness and perceived ease of use. A dependent variable is the variable being studied and measured in Research. In the Perceived Usefulness model, perceived Usefulness is the dependent variable. The model has six hypotheses: attitude toward using technology is the mediating variable, while computer self-efficacy is the moderating variable.

Variables are resources a researcher uses to create a statistical model. A dependent variable, in this context, is the feature or factor that is expected to change and vary as a result of numerous causes or independent variables in the model (Faeq et al., 2022). In simpler terms, in Research that relies on data, the results provide formulaic illustrations that link independent variables, the concepts, measurements, or background phenomenon under examination, to a measurable dependent factor. Filipović, 2022 said that it usually supports well-articulated and open inquiry to guarantee valid and reliable results. Within the theoretical model of Perceived Usefulness, the dependent variable identified is technology use, which consists of user actions triggered by information provided on technology products.

The users may accept or reject the tech tool that depends on perceived Usefulness (Gomes & Lopes, 2022). As a result, mediating variables factors that affect and direct the correlation between the independent and the dependent variables such as social influence, lifestyle compatibility, or perceived ease of use considerably influence acceptance behavior. Defining features can bear significant moderating variables, such as compatibility, an exceptional impact contingent on users' time, and behavioral attitude also creates a leading factor that decides how to ease acceptance (Gupta & Harvey, 2022). Perceived Usefulness forms an integral part of Research. Under this hypothesis, express conjectures drive usability appraisal, advocating studies of how individuals perceive utility ascribed to using a solution or device technology, which exemplifies potential brain shakers. Six hypotheses underlying this Perception of Ease model unravel from quantitative studies and deriving web surfer acquisition.

1. 'Facilitating Conditions' supposes that either organization access or relevant staff nurturing appropriate priorities contribute significantly to perceptions of usability benefit.
2. 'Social Influence' declares that behavior by friends also advocates stakeholders' respect for clients' notions and leads them appropriately to cater to options deemed on perspective (Henriksen et al., 2022).
3. 'Perceived Usefulness' indicates intensity by adding within a domain susceptible impression find deliverability adequately induces satisfaction making User acceptance tangible despite some challenge if readily perceivable per location.
4. 'Perceived Trust' is a possible meaningful authentication degree concept relation channeled through corresponding relevance in giving a tech note proficient server use results (Hina et al., 2022).
5. 'Perceived Enjoyment' states that interpersonal linkage partially framed by learned enjoyment derived from browsing the web has association web click optimization too slow for uptake conventional connection shapes mediated behavioral response assessment aid reciprocations belief construct a hypothesis (Jasim et al., 2022).
6. 'Lifestyle Compatibility' presupposes personal predial elect distinctive qualities notably results urgency invested corresponding solutions somewhat implied by demand circumstances (Luo et al., 2022). Worth simultaneously ensuring expected plans are realistic given situations, aids viable investment mechanisms that moderate external competition depending on adoption costs, supports structure practices for better accuracy response rate optimization dictates final preference selection strategy guidelines.

In closing, identifying an accurate and valid daily-life-related dependent variable within conceptual model testing focuses mainly on Research (Malodia et al., 2023). Scientists stand to continually present Research logically connect independent origin purposes guiding because reasonable intermediary that distances requisite hypothesis testing namely moderating expectations to authentically good significant computing empowering problems facing much processing methodologies implementing infrastructure building blocks brought about computer technology explorations.

Overall, understanding the concept of a dependent variable is crucial in conducting quantitative Research (Olaleye et al., 2022). The Perceived Usefulness model provides us with one such dependent variable: technology use. The model also presents six hypotheses that can be used to evaluate users' perception of usability benefits. Ran et al., 2022 said that by understanding the mediating and moderating variables, such as social influence, lifestyle compatibility, or perceived ease of use, we can identify the factors that affect and direct the correlation between the independent and dependent variables. It helps us conduct a well-articulated and open inquiry to ensure we achieve valid and reliable results. Therefore, researchers need to continue exploring new methods and technologies to enhance the accuracy and efficiency of their Research.

The advent of the internet has provided consumers with greater convenience in purchasing (Rietmeijer & Veen, 2022). Online food buying has become popular among individuals as internet penetration has grown, and the availability of online food ordering services is becoming widespread. With the increasing demand for online food buying, it is vital to establish the factors influencing consumer buying behavior (Sefton et al., 2022). The study aims to identify the factors that drive consumers' interest in online food buying. Several potential factors may motivate people to order their food online. In order to identify these factors, a questionnaire is being designed to survey consumers about their perceptions, preferences, and habits for online food ordering. 

Research Question: What factors influence a consumer's interest in online food buying? 

Survey Design: The questionnaire will be used to collect data from consumers who have used online food ordering services (Silva et al., 2023). The survey can be conducted online or in person. The survey will consist of 20 questions, divided into three sections - demographic information, ordering behavior, and opinion-based questions. The demographic information section will help categorize the responses according to age, gender, and education. According to Tittarelli et al., 2022 the ordering-behavior section will involve questions directly associated with the consumer's order-making process, such as the number of orders, the time to place the order, and the average expenditure per order. Finally, the opinion-based questions will provide an understanding of the consumer's opinions and expectations for online food ordering. The questions will cover potential factors affecting a consumer's decision to order food online, such as convenience, speed, availability, and price. Data Analysis: The results from the survey will be analyzed using the appropriate statistical techniques. The analysis will identify the factors that are significant in influencing consumers buying behavior of online food purchases. Identifying these factors will help food companies to understand and address what drives consumers to order their food online. 

As the prevalence of e-commerce continues to expand, the food industry has not been left behind. Consumers are using internet marketplaces to buy food in more significant numbers (Tran & Kim, 2022). It is crucial to comprehend what drives people to purchase food online. A questionnaire will be developed to survey consumers and collect their responses to achieve this goal (Bhutta et al., 2022). The first section of the questionnaire will address the consumers' demographic information. Participants will be asked to provide information such as age, gender, educational level, and employment status. This information will aid in identifying trends among different consumer groups. The second section of the questionnaire will focus on the consumers' online shopping habits.

Participants will be asked how frequently they engage in online shopping, what products they purchase, and their preferred payment methods (Debrah et al., 2022). These questions are crucial in examining consumers' behavior toward online shopping and will provide a foundation for food industry-specific inquiries. The third section of the questionnaire will delve into the factors that influence consumers' interest in online food buying (Din et al., 2022). Participants will be asked to rank the most important factors, such as convenience, pricing, quality, or variety, followed by open-ended questions, where they can offer further elaboration or insights about their choices. Finally, the questionnaire will address consumers' experience with online food shopping. Participants will be asked to provide feedback on the ease of use of food delivery websites, the ordering process, delivery time, and product quality. 

Conducting an interview can be a powerful research method to gather firsthand information and opinions about a specific topic (Enholm et al., 2022). A critical aspect of running any discussion is the selection of the ideal respondent who can provide insightful and relevant information. Choosing the appropriate candidate from the target population is crucial to make the most of the interview process. Selecting the ideal respondent may depend on the specific topic of the research project. Faeq et al., 2022 discuss that in many cases, targeting individuals with direct experience and knowledge relevant to the issue is beneficial. For instance, if researchers are interested in gathering information about the impact of big data on the healthcare industry, they may consider interviewing healthcare professionals who deal with data management processes. Alternatively, it may be beneficial to interview patients who have accessed healthcare services utilizing big data. By selecting respondents with firsthand experience in the domain studied, researchers can gather authentic insights to provide a more fulsome understanding of the research area.

Finding individuals for the interview process can be approached in various ways. One strategy would be to draw on existing contacts or social networks related to the topic of study (Filipović, 2022). In other scenarios, the snowball sampling technique may come into play, in which current respondents suggest additional people or professions\selections to target, gradually building a broader knowledge base. One must always look to adequately diversify this approach to avoid researchers becoming limited to a very constrained cohort of conditions\read-through continually expanding recruiter’s online platforms, contacting individuals through LinkedIn, academic or professional bodies (Gomes & Lopes, 2022). Once an evolution-oriented list of potential respondents is identified, researchers can initially evaluate and then finalize the list. It could involve the pre-approval of the respondents via an informed consent form mentioning legal authority, confidentiality, and connection policy with people within confidential dependencies.

In an interview, it is essential to identify the ideal respondent to provide valuable insights and information relevant to the research (Gupta & Harvey, 2022). The ideal respondent will possess knowledge or experience related to the research topic that can offer valuable and credible information or provide a unique perspective that can enhance the understanding of the subject matter. One needs to identify relevant people or organizations that house the ideal respondent to approach the ideal respondent. In some cases, referrals from the respondent's network facilitate identifying the ideal respondent (Henriksen et al., 2022). Twitter, Facebook, and LinkedIn are just a few examples of social media sites that can be used to find possible responses. These platforms provide valuable information such as work experience, educational background, and other pertinent details about potential respondents. When approaching the respondent, presenting the research project clearly and concisely is essential. The respondent should be informed of the research's purpose, the nature of the questions that will be asked, and the duration of the interview. The respondent's ownership of the information they provide should be emphasized; this helps to foster an open and honest interview.

Furthermore, selectivity, phrasing, and enforcing professional, ethical formation for or in these consents with willing, open, authentic responses during the interviewing can revendicate plus upon directing assignment report analysis. Always get approval over terms about seeking honest answers and avoiding social or economic provocations while analyzing the arrangement (Jasim et al., 2022). Researchers suggest that selecting the ideal respondent can affect the interview's uniqueness, information quality, and ultimately, the value of the resultant data collected something to remain alert towards\ to ensure this section reaches its fundamental objectives.

Reference

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