Ford Australia Facing Revenue Losses Measuring Validity and Reliabili

Question: Describe about the Ford Australia Facing Revenue Losses for Measuring Validity and Reliability. Answer: Introduction The paper helps in providing a research proposal in respective of the business problem of an organization including the dependent independent variables. The proposal aims at addressing the quantitative research methodology to instigate the business problem. The project also deals in measuring the variables, specifying and justifying the hypothesis, developing the questionnaire, identifying the sampling design, and selecting an appropriate data collection mode for critical conduction of successful quantitative business research. The main objective of the research is to achieve the learning objective in regards to identifying the business opportunity for the synthesis of the literature, application of the proper methods, design and plan for the research by identifying the quantitative research methodologies and ethical issues related to the business research. Background The Australian blue oval car brand, Ford has been ended in the year after the company posted a loss of $191 million in the country since 2014 (Martin, 2014). The year has been marked as the historic low since 48 years. This brings Ford Australia to total losses of astounding $1.3 billion since the last 10 years during which the time has received over $ 1.1 billion in the funding of the government. Ford has been able to post the profit of three years of the last decade since the loss alone in the year 2014 (Klyatis, 2015). The profit of the car company has reported an estimate of $ 186 million over an entire decade. The company had been posting a profit since 3 years of the past decade. Since 2014, the company has been facing losses due to the evaporation of the profits that the company has reported over and entire decade which was estimated to be $ 186 million (Fields et al 2013). According to the company, $ 157 million of the $ 191 million has been lost on other cost associated with the closing of the factory since October 2016 (Martin, 2014). There has been one silver lining on the results review operating the loss for the rest of the companys business which has been making more profit per vehicle against selling of the cars. Literature review Measuring the reliability and viability of the dependent variables Validity According to Csikszentmihalyi Larson (2014), a variety of factors helps in affecting the extent to which an operational definition of a variable can be constructed on the basis of the validity. The complexity of the concept of the variables : According to Homburg Bornemann (2013), some variables are not very complex and is determined by the general chapters physical attributes. However, they also believe that most of the variables are straight forward. The physical dimension of the expression and important differences in the variables affect the business performance which are conceptual variables addressing the problems of operationalization of their own. Availability of data: According to Lussier Corman (2015), the operationalisation of the business seems to capture the perfectly underlying variable of interest. The number of assets, expansion of business, growth for sales and profitability of the business are some of the reasons for reviewing the records to compile the information drastically less than perfect operationalization cannot be employed due to the lack of ideal data. Cost and difficulty in obtaining data: According to Park Lee (2014), reviewing the records and measuring of the business organization availability of data is a very crucial factors where is availability of data can be evaluated by the collection of relevant data related to the business organization which requires both time and money. Thus, it is very crucial for the researcher to conduct a survey and get the desired information in a quick and easy manner. The above were some of the reasons which provided a great deal of the validity of the research centers around the problems of the organizations. As a matter of fact, most of the debate surrounding the quantitative research not actually about the analysis method or outcome of the research but also about whether the variables have been defined as measured in appropriate manner. According to Carland Carland (2015), unless and until the operational criteria for measuring the variable are sensitive to the variable that actually changes, they would be generating relating outcome for free research topic. Reliability Reliability is the consistency of repeatability of a business process. On the other hand validity is the measurements of the item of interest it is very important to distinguish between the validity and reliability. Acording to Csikszentmihalyi Larson (2014), the reliability focuses on the consistency of the measurement. According to their four types of measurement scales nominal, ordinal, interval and ratio. The nominal scale is the classification by the name which can be formed on the basis of some measurement criteria the purpose of the scale is just for identification of the factors responsible for influencing the revenue growth of the organization. The ordinal scale measurement helps in providing a rank order by knowing the ranking of the score in order to provide information about the performance of the organization. The physical dimension of the expression and important differences in the variables affect the business performance which are conceptual variables addressing the problems of operationalization of their own. The interval measurement scale helps in measuring both the order and the size of the different scored in order to determine rank order. The ratio measurement scales in defining the scores that have similar qualities to the others during first time and distance score. The standard scores are helpful in comparing the performance of the organization in the market. The measurement scale needs to covert to the some score measure without which it is impossible to completely convert the two scores into similar scale. The commonly used measurement scales include the liker scale, semantic differential, and rating scales. The likert scale involves the 5 to 7 point scale which responds in corresponding to the level of agreement (Lussier Corman, 2015). The semantic scale uses bipolar adjectives ranging from positive subjective scores to least positive scores. Similarly, the rating scales are frequently used in research. According to Csikszentmihalyi Larson (2014), it would be better to create evaluation devices that will reduce the need for value judgment and subjective requiems such that to help in evaluating the efficiency o f the business organization in a better way. Types of scale According to Homburg, Stierl Bornemann (2013), the statically analysis of the business organization requires field measurement of the dependent variables influencing the analysis technique. The measurement needs to be carried out depending on the type of information involved in the type of the analysis. Although, the measurement and procedure of measurement may differ in ways they can be classified using fundamental categories like the nominal scale measuring unit uses a nominal scale which simply categorizes the responses, revenue, profitability, performance related to a business organization. According to Csikszentmihalyi Larson (2014), the most important feature of the nominal scale is that it does not imply on the offering among the responses. Variables to explain reliability and validity properties According to Lussier Corman (2015), the sales of the firm is an independent variable that influences the metrics such as the growth of the sales revenue for the firm. Again, the customers service standards is an another indecent variable that influences the perceptions of the customers in respective of their purchasing decisions. Hypothesis H1: Innovation in the manufacturing process would be helping in affecting the revenue growth H2: Customer service is an important dependent variable that helps in influencing the revenue growth H3: Increment in sales would be helping in increasing the revenue. H4: Implementation of appropriate marketing technique would be enabling the organization in increasing the revenue growth Corporate life cycle theory The theory depicts the model of evolution of the businesses by describing the progression of the organizations through multiple phases and factors. The theory helps in illustrating the growth and measurements related to the business organizations in the market. According to the theory, growth of a firm is a process faction which is influenced by the change in some of the variables. The theory depicts that the measures of the growth rate of the forms are inter dependent and inter related. Based on the theory, the various factors faceting the growth rate of the firm can be illustrated by the following diagram: Conceptual model Figure 1: Conceptual model for factors affecting the revenue system Source: Created by author Develop and justify questionnaire Q1: What are the independent and dependent variables affecting the profitability and the revenue growth in a business organization? The above questionnaire would be helping the researcher to gain valuable and adequate information related to the various factors that help in affecting the revenue growth and profitability of the business organization. Factors affecting the information related to the questionnaire As the questionnaire is information sensitive, lot of employees would be reluctant to disclose the confidential information related to their business organization. Moreover, there is also a possibility of biasness in the response of the employees as the information is susceptible to the reputation of the organization. Research plan Population In order to collect quality and useful information random sample of respondent should be selected for the construction of the survey the respondent should be belonging to the organization that would be providing with the valuable and adequate information related to the research topic. Moreover, the conduction of service should be based on the questionnaire which should be provided to the respondents in order to collect the information. Sampling frame Figure 2: Sampling frame for the research process Source: Created by author Conduction of sampling frame Sample Frequency Population (%) Gender Male 66 56 Female 57 44 Age 24-35 35 32 35-50 56 45 51 above 26 23 Hierarchy level CEO 8 4 Manager 54 25 Supervisors 45 32 Workers 63 39 Table 1: Sampling frame for Ssmpling data collection Source: Created by author Target sample size The main objective for the Data Collection process is to collect 100 samples from the respondents which have to be randomly selected. The respondents would be responsible to provide useful and adequate information related to the research topic on the basis of research questionnaire been set in the research process. Data collection mode In order to collect data for the research process, a sample form should be created which should be containing the set of questionnaires as prepared in the research paper. The questions content should be listed in the form multiple choice questions on an individuals basis such that the respondent would be able to provide their opinions on the basis of the questionnaire related to the research topic. The conduction process of Data Collection should be conducted in the form of survey. This survey should be requiring the respondents to fill up the research questionnaire forms belonging to the organization being selected for the resources the employees of the organization including the CEO, managers, supervisors and the workers of the organization acquired information.. Reviewing the records and measuring of the business organization availability of data is a very crucial factors where is availability of data can be evaluated by the collection of relevant data related to the business orga nization which requires both time and money. Thus, it is very crucial for the researcher to conduct a survey and get the desired information in a quick and easy manner. The conduction of the survey on the basis of the research topic requires the respondents to fill up the research questionnaire forms information of trains with the survey would be helping in providing the precision in respective of the data accuracy to a level that the information being acquired in the requested is relevant and valuable to the research topic Analysis of data Data analysis technique could be focusing on the quantitative analysis. The conduction of the quantitative analysis approach would be helpful in making the outcome of the research process to be more productive in respective of research study being selected (Byrne, Jordan Welle, 2013). This quantitative approach would be helping the researcher to gain appropriate knowledge about the research topic based on the responses as provided by the sample respondent in respective of the business problems related to the case organization. Ethical implications While conducting the research survey, the researcher needs to follow the following code of conduct while implementing the research process: Confidentiality: While conducting the survey, the researcher needs to keep the information confidential enough such that the data remains safe from reaching the unsafe hands of an outsider or is miscued in the process (Bell, 2014). This maintenance of the confidentiality of the information being collected in the research process should be the major priority of the while conducting the research process. Integrity: Data integrity is another aspect that the researcher meds to consider during the implementation of the research process. The integrity of the information is to be maintained in the sense that it is not altered or modified by any means during the condition of the research process. Privacy: Data privacy is another important aspect of any ethical code of incite which requires the information to be safe and secured in order to prevent the same to be exposed to the outsiders. Thus, the researcher is required to destroy they confidential information after the meeting of all the objectives of the research process. References Aaker, D.A. (2012) Building Strong Brands, 2nd ed. London: Simon Schuster. Bell, J., (2014).Doing Your Research Project: A guide for first-time researchers. McGraw-Hill Education (UK). Byrne, M.D., Jordan, T.R. Welle, T., (2013). Comparison of manual versus automated data collection method for an evidence-based nursing practice study.Applied clinical informatics,4(1), pp.61-74. Carland, J.W. Carland, J.C., (2015). A model of potential entrepreneurship: Profiles and educational implications.Journal of Small Business Strategy,8(1), pp.1-14. Crouch, C. Pearce, J. (2012) Doing Research in Design - Page 68, 2nd ed. London: Bloomsbury Publishing Plc. Csikszentmihalyi, M. Larson, R., (2014). Validity and reliability of the experience-sampling method. InFlow and the Foundations of Positive Psychology(pp. 35-54). Springer Netherlands. Figliozzi, M. Blanc, B., (2015).Evaluating the Use of Crowdsourcing as a Data Collection Method for Bicycle Performance Measures and Identification of Facility Improvement Needs(No. FHWA-OR-RD-16-04). Freling, T.H. Forbes, L.P., (2013). An empirical analysis of the brand personality effect.Journal of Product Brand Management Homburg, C., Stierl, M. Bornemann, T., (2013). Corporate social responsibility in business-to-business markets: how organizational customers account for supplier corporate social responsibility engagement.Journal of Marketing,77(6), pp.54-72 Klyatis, L., (2015).Introduction to Successful Predicting of Product Performance (Reliability, Durability, Safety, Quality, Recalls, Profit, Life Cycle Cost, and Others)(No. 2015-01-0487). SAE Technical PaperMurty, K.S., Fields, M.M., Herd-Clark, D.J., Vyas, A.G., Hill, E.L., Wyche, B., Byrd, D. Shavers, S.R., (2013). CONGRESSIONAL PROGRESSIVE CAUCUS AGENDA: CHALLENGES AND OPPORTUNITIES FOR 2012 ELECTIONS.Race, Gender Class,20(1/2), p.56. Lussier, R.N. Corman, J., (2015). A business success versus failure prediction model for entrepreneurs with 0-10 employees.Journal of Small Business Strategy,7(1), pp.21-36 Martin, T., (2014). Transport: Getting some new wheels.Connected Home Australia, (Dec 2014), p.50. Palinkas, L.A., Horwitz, S.M., Green, C.A., Wisdom, J.P., Duan, N. Hoagwood, K., (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research.Administration and Policy in Mental Health and Mental Health Services Research,42(5), pp.533-544. Park, J.G. Lee, J., (2014). Knowledge sharing in information systems development projects: Explicating the role of dependence and trust.International Journal of Project Management,32(1), pp.153-165. Robson, C. McCartan, K., (2016).Real world research. Wiley. Rosenbaum-Elliott, R., Percy, L. Pervan, S., (2015). Strategic brand management. Oxford University Press, USA.