supply chain discussion question and two student reply
Discussion Question:
Describe the major challenges the transportation industry is facing in the current environment. Respond to your peers and cite your work.
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Vanessa Greenlee The major challenges that the transportation industry is facing today is the cutting of transportation logistics cost. One major way they are cutting transportation cost is consolidating the bulk shipments and putting them all in one truck load. The problem with this is that it may delay deliveries and also impact the customer satisfaction negatively. Of course the transportation industry is having a really big shortage in truck drivers. Where I work we see it a lot when trying to schedule a truck for a load picked up it has been a nightmare. Trucking companies either don’t have the man power or they don’t have certified truck drivers to take a hazmat or a classified shipment. These challenges definitely affect the shipping department and the receiving party. Another major challenge is having to comply with the government regulations. Federal Motor Company safety administration (FMCSA) had a law in place for truck drivers that limits them to the amount of hours they are on the roads. So for example truck drivers could only drive five hours at a time then had to take a break. However in March of 2020 the FMCSA temporarily waived the working hour limit so that truck drivers could meet the demands during the stay at home orders period now that the stay at home orders are lifted truck drivers have to follow the FMSCA’s guidelines again.
https://www.dispatchtrack.com/blog/top-transportat…
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Matthew Prather The top 3 significant challenges that I found in the transportation industry in our current environment are drivers shortages, retention, and driver compensation. There is a driver shortage partly due to everything opening up after the covid-19 crisis. The supply of shipments to reach the consumer’s demand requires more drivers to move these supplies from place to place. However, there are very few drivers because they either quit or are suffering from the virus known as covid-19. Speaking of health concerns, many drivers left due to the retention of the transportation industry involvement in handling the pandemic. Let us be honest no one handled this virus well, and the whole logistic industry suffered because of the decision of the consumer and the supplier. Safety conditions skyrocketed, and drivers put their life on the line while moving these supplies that could carry the virus. Many got sick or died of this virus which caused the rest of these truck drivers to consider early retirement. Another big issue for the truck transportation industry is that these drivers are not getting the proper compensation for their work. These truck drivers are stressed out with dealing with outrageous deadlines for the time required to deliver these supplies. On top of that, truck drivers are hauling full loads and are constantly on the road. These drivers need to be compensated for every mile or week that they have been on the road. Truck drivers also need hazard pay, the amount of the load size, and receive extra pay for delivering the load on time. Overall I believe that the transportation industry will eventually get ahold of this pandemic and handle the consumer’s demand better with qualified drivers.
resource: https://www.transportdive.com/news/ATRI-driver-concerns-trucking-retention-pay-2021/608797/
done
Seen
few seconds ago[supanova_question]
Research Proposal (3000 words) Title of Topic/Project Proposal An Investigation of the
Research Proposal
(3000 words)
Title of Topic/Project Proposal
An Investigation of the Barriers Hindering Artificial intelligence in SME’s.
Introduction:
The proliferation of information technology has leveraged dramatic advantages to individuals, businesses, and many other facets of human life. These advantages are primarily attributed to the adoption of different computing technologies that enhance automation, speed, and efficiency. Artificial Intelligence is a crucially important technology that has developed new technologies and systems that simulate human behaviour and automate business operations (Aarstad & Saidl). The business world has undergone drastic changes, and vast technological advancements accrued from Artificial intelligence. In fact, research posits Artificial Intelligence as the greatest technology because of the immense commercial opportunity it presents to businesses, promoting the fast-changing economy.
A plethora of research asserts Artificial Intelligence as a great opportunity for businesses, particularly in the highly competitive economy characterized by immense opportunities and technologies. This has resulted in the high adoption of the technology in most businesses to establish a competitive advantage. Technical reports and seminars infer that most businesses have reported wider margins and increased sales through such technological facets. However, these effects are limited to large companies, which have shown a greater interest in adopting the technology. Aarstad and Saidl notes that only 5% of small and medium-sized enterprises (SMEs) have adopted Artificial Intelligence in their usual operations.
Consequently, SMEs are underrepresented among AI adopters in the business industry. This is because of the negligible statistics occasioning the rate of AI deployment among this facet, inferring the limited benefits to SMEs. With the increased implementation of the technology among businesses and individuals and the drastic impacts leveraged by the adopters, there is a need to investigate the low adoption rate among small and medium-sized enterprises (Alsheibani, Cheung & Messom, 2019). The focus of this thesis is to investigate the barriers hindering the adoption of Artificial Intelligence among small and medium-sized enterprises.
The concept of the low adoption of Artificial Intelligence in SMEs remains a pertinent area of debate, given the substantial advantages accrued by adopters of the technology. Aarstad and Saidl maintains that the barriers hindering SMEs’ adoption of Artificial Intelligence can be classified into technological, organizational, and environmental. Each of these contexts has a magnitude of effect on the adoption of the technology. Alsheibani, Cheung and Messom (2019) outlines the barriers of AI adoption and categorizes them as organizational, environmental, and technical. On the other hand, the paper posits legislative standards, management, and workforces as the core facets hindering AI adoption. Evidently, these sources and other analytical studies conclude that the slow AI adoption in SMEs is attributed to organizational, technological, and environmental facets, which shape the rate of technology adoption among SMEs.
Theoretical Background and Research Focus:
According to Alsheibani, Cheung and Messom (2019), the rise of information technology and other computing technologies like Artificial Intelligence has necessitated the rapid change and growth of businesses in a fast-changing and competitive economy. The authors posit Artificial Intelligence as a strategic technology that businesses should leverage for competitive advantage. On the other hand, the study focuses on exploring the factors inhibiting the adoption of artificial intelligence among businesses. The authors explore this research area to understand the underlying barriers of AI adoption to promote effective recommendations for flawless adoption.
The hypothesis centrally focuses on the determination of the stage of AI adoption in Australian organizations and the identification of the barriers that can be overcome to speed up the adoption. Resultantly, the researchers classify the barriers of AI adoption into three categories. These are organizational, environmental, and technical barriers. The environmental barriers of AI adoption focus on the consumers, the government, and ecological factors. Lack of an efficient alignment between the environmental facets and the technology posits the slow adoption. On the other side, the study postulates technical barriers as core hindrances in AI adoption (Alsheibani, Cheung & Messom 2019). These refer to adequate training and expertise, the technical know-how, data, and other tools required in the technology. These are critical as they form the base foundation of the adoption.
Lastly, the authors advance organizational barriers as critical hindrances in AI adoption. Here, the firm and its internal structures play a crucial role in favoring the deployment of technologies. For instance, some employees prefer interacting with human facets to robots and expert systems, core AI technologies. Such poses critical impediments to the implementation of robotics and expert systems (Alsheibani, Cheung, & Messom 2019). Also, the firm’s size, the costs of technology, government regulations, and stakeholders’ stance on the technology affect adoption.
The study results posit the rate of AI adoption in Australian organizations in general. The generalized research findings can be extrapolated to the area of study. Here, the research results are substantial in addressing the common barriers of AI adoption in all organizations. In fact, the small and medium-sized organizations have vast effects from the outlined barriers. Organizational barriers, for example, include facets such as cost and size of a firm, which determine the need and capacity to adopt new technologies (Alsheibani, Cheung, & Messom 2019). Most SMEs face cost and capacity challenges, failing to adopt such technologies. On the other hand, technical expertise and IT skills are vital. However, SMEs have limited jurisdiction in this area, as most firms have limited employees who might lack the technical expertise required.
Aarstad & Saidl assert Sulaiman’s research and findings. According to the authors, the gap in AI adoption between SMEs and large companies is vast. The study, which focused on European firms, determines that only 5% of SMEs have adopted and utilized Artificial Intelligence technologies in their businesses. A comparative analysis with the larger organizations shows the tremendous advantageous and competitive advantage of large firms using Artificial Intelligence. A review of the digital transformation in SMEs identified that various facets hinder the adoption of current technologies among SMEs. Besides, the authors adopted the Technology-Organization-Environment (TOE) model as a research lens to define and categorize the barriers of AI adoption (Aarstad & Saidl).
The study hypothesis focused on the determination of the constraints hindering the adoption of Artificial Intelligence in small and medium-sized enterprises. Resultantly, the TOE framework and Digital Transformation analysis determined the following concepts as crucial constraints. These include organization readiness, digital transformation capabilities, resources, strategy, perception, ecosystem requirements, and technology accessibility are fundamental barriers of AI adoption in SMEs (Aarstad & Saidl). Resultantly, the study adopts the TOE model to categorize the barriers of AI adoption in SMEs.
Thus, the paper posits the technological, environmental, and organizational context as core hindrances for AI adoption. Under technological context, the authors note a variety of concerns likely to affect technology implementation. These include the organization’s technical fitness, their understanding and conception of AI, data ecosystem, the perceived negative effects of the technology and other similar technologies, and the proposed value of the technology to the firm (Aarstad & Saidl). On the other hand, the organizational context leverages huge impacts on the adoption of such technologies. For instance, the paper notes some of the prevalent organizational hindrances. These are attention to technological facets, need for automation, human resource capabilities, organizational resistance, potential investment plans, proposed benefits, perceived risks, and transformation constraints.
Lastly, the study categorizes the constraints as environmental factors. These are factors within the firm’s environment that hinder AI adoption. For example, AI expertise might seem like a technical factor, but it is also an environmental facet. Here, lack of AI competence and talent and cost of AI technologies affect the rate of implementation (Aarstad & Saidl). Besides, consumers’ concerns have a great impact on deploying technology. For instance, skeptical consumers might be against the technology, hindering adoption. On the other hand, industrial factors may affect adoption. Here, certain technologies might slowly be adopted by different industries, affecting the overall adoption. The paper maintains that legal constraints and risk perception determine the deployment of technologies.
Technology Acceptance Model:
The proliferation of information technology has promoted the adoption and implementation of innovative technologies. Businesses and individuals leverage such technologies to automate their operations and establish a competitive advantage over rivals. While the perceived benefits of innovative technology adoption are vast, the rate of deployment varies among different consumers of the technology. Najib and Fahma (2020) deployed investigative research to determine the rate of acceptance and deployment of innovative technologies among small and medium-sized enterprises. The study focused on investigating the adoption of digital payment systems in SMEs.
Resultantly, the authors used the TAM model to understand and categorize the resulting cognitions of the study question. This necessitated the following. First, the rate of adoption of innovative technologies, as defined by the technology acceptance model, is defined by adopters’ factors. These may include facets like perceived usage, benefits, strategic risks, and affordability, and access to the required technologies. The model further notes the intention of using innovative technologies is core in determining its adoption rate. Understanding the perceived usefulness and ease of usage of an innovative technology impacts consumers’ intention to adopt and use the technology (Najib & Fahma, 2020). The research shows this as a fundamental model to understand consumer behavior. Here, understanding the rate and drivers of technology acceptance can reveal important facets and hindrances of adopting innovative technologies in SMEs. According to the study, adopting the defined technology was majorly affected by the type of digital technology, ease of use, the usefulness of the technology, and reasons for use (Najib & Fahma, 2020). This can be extrapolated to AI adoption in MSEs with specific reasons being outlined.
Aim of the study:
The aim of the study is to investigate the barriers hindering the adoption of Artificial Intelligence in small and medium-sized enterprises. To better understand the barriers hindering the adoption of AI in SMEs, the study will aim at answering the following questions and meet the specified objectives.
Research Questions:
What are the barriers preventing SMEs from using artificial intelligence to strengthen their business?
What internal factors in small and medium-sized entities prevent businesses from adopting artificial intelligence?
What external factors have contributed to the low adoption of artificial intelligence by SMEs?
Research Objectives:
The following are the objectives of the study:
1. Investigate the barriers hindering the adoption of artificial intelligence in small and medium-sized enterprises.
2. Identify the barriers preventing small and medium-sized enterprises from using artificial intelligence to strengthen their businesses.
3. Investigate the internal factors that prevent small and medium-sized entities from adopting artificial intelligence.
4. Determine the external factors that contribute to the low adoption of artificial intelligence in small and medium-sized enterprises.
Justification and Contextualization:
Most small and medium-sized entities encounter challenges in the adoption of artificial intelligence. According to Aarstad and Saidl, only 5% of SMEs have adopted artificial intelligence putting them behind larger organizations. Research has identified that small and medium-sized entities spend less on it compared to larger organizations. Such entities also encounter problems with matching their human resources with the proper knowledge and skills for handling artificial intelligence. Alsheibani, Cheung and Messom (2019) identify environmental challenges as a problem inhibiting artificial intelligence adoption. Besides, the study posits the technological and organizational barriers that hinder the seamless adoption of Artificial intelligence.
On the other hand, Aarstad and Saidl outlines the advantages of innovative technologies in the fast-changing world. Here, the early adopters of technological advancement may leverage huge advantages and develop a competitive advantage, which sets and their businesses apart. This results in improved economic returns and organizational growth. The rate of AI adoption in SMEs is worrying. This needs a revitalized strategy to enable maximum utility for growth and competitiveness in SMEs.
As outlined earlier, the primary aim of the research is to investigate the barriers hindering the adoption of artificial intelligence in small and medium-sized enterprises. This is important as it will help entities and organizations to understand the barriers and leverage the technology in business operations (Ghobakhloo & Ching, 2019). First, the research will help in the determination of fundamental barriers to AI adoption in SMEs. This will help many organizations to understand the reasons for their lagging behind in technology acceptance. Second, the study will help define specific internal and external factors that prevent AI adoption in SMEs. This is vital, as it will address specific organizational barriers, promoting structural changes and recommendations for such firms.
According to researchers, the growth and development of information technology have resulted in fast-growing economies. Here, businesses and operations are characterized by vast innovative technologies that offer an upper hand in trade and automated business functions. This infers that artificial intelligence and other innovative technologies are growth opportunities for businesses (Alsheibani, Cheung, & Messom, 2019). Here, businesses must effectively utilize these technologies for automation, speed, and other innovative capabilities. On the other hand, statistics infer the low adoption of the technology among SMEs.
Thus, the study results will not only identify the barriers but also inform the adoption of the technology among SMEs. For instance, the identification of the barriers is paramount. This is like identifying the problem, which promotes problem-solving. Similarly, the study findings will promote a structural and industry-wide approach to promote the adoption of artificial intelligence in SMEs. The study is important, as its results will work as a guiding framework to help SMEs leverage innovative technology for effectiveness (Ghobakhloo & Ching, 2019). Therefore, it is vital for the identification of the study findings. On the other hand, the research findings will help firms and organizations in developing organization and industry-wide strategies to utilize and adopt artificial intelligence.
The wide gap of artificial intelligence adoption between large organizations and SMEs is vast. Notably, the benefits and impacts of the technology and other innovative technologies are evident among the adopter firms. Understanding the barrier and hindrances of AI adoption in SMEs is a research gap that requires substantial studies. This study will promote the area of growth and development among SMEs. Here, while the gap in AI adoption between large and small enterprises is a challenge, identifying the challenges will have a substantial impact on the research area (Stentoft et al., 2019). The study will promote timely and current research evidence to address the gaps in the economic growth of firms, given their sizes.
Lastly, the study is critically important as it addresses current research and organizational need. The organizational, environmental, and technical barriers identified have an ultimate effect on firms and their technology acceptance attitudes. These hinder technological developments and innovativeness, which predisposes organizations to highly competitive and growth capabilities within their industry. Also, the need to develop and deploy technological aspects in organizations is inevitable today. Therefore, SMEs, which are the least adopters of AI technology, require substantial information to tackle their limitations and implement these effective technologies (Radhakrishnan & Chattopadhyay, 2020). The study will provide essential findings that will enhance structural strategies to promote artificial intelligence adoption in SMEs.
Methodology:
The study will employ qualitative research methods to collect and analyze numerical data for statistical analysis. Primarily, the researcher will use interview and survey methods to collect primary data from respondents. These methods are the most effective strategies for this type of research design, as they offer non-biased and quality data for research. The study will deploy these to observe and understand organizations’ perceptions and attitudes toward technology and innovation in businesses. Interview questions and questionnaires will be administered in face-to-face interaction. The qualitative method will focus on interactionism theory by George Mead to identify various facets vital to determine barriers of artificial intelligence adoption in Small and Medium-sized Enterprises.
The study will target manufacturing SMEs with a capacity of between 10 and 250 employees. This will enhance the scope and special focus on a given and specific population. The study will employ a sample size of approximately 400 respondents. Public databases and manufacturing industry information will be leveraged to identify manufacturing SMEs. The organizations will be selected using the industry and capacity data. The eligible firms will be subjected to the research using the methods listed above.
Research Design, Research Approach, and Research Type:
The study will follow a field research design, where respondents will be interviewed in their natural environments. Studying the respondents, their perceptions, and attitudes in the subject of analysis will help determine the primary barriers hindering the adoption of artificial intelligence in SMEs. The study will use a qualitative research approach to collect and analyse data. Interviews and survey questionnaires will be the primary data collection methods. Data analysis will involve statistical methods to find causes, experiences, and hindrances to artificial intelligence in SMEs. In analysis, structural analysis programs will be used to code, analyse, and evaluate the research findings. For instance, the findings and barriers will be categorized into three main clusters: environmental, organizational, and technological contexts. Data analysis will follow a thematic analysis and structural analysis to determine each barrier, informing the primary research question and research objectives.
Access to Data and Research Ethics:
Access to the research field is a fundamental task relating to this study. To achieve this, the researcher will employ the following. First, the researcher will use endorsements from authorities to get access to respondents. Second, the researcher will seek and encourage honest cooperation by defining the impacts of the involvement to both the firm and the study. Third, the researcher can offer appropriate and acceptable incentives, openly appreciate respondents, and get third-party approval, particularly those in charge of the respondents. On research ethics, the study will focus on the two broad categories, researchers’ relation with methodological standards and their relation to the surrounding, particularly data subjects. The researchers’ primary focus will be on constructive critical openness, respect, and ensuring good consequences for the study and society.
Limitations:
This research study’s primary limitations will result from the research methodology adopted. Qualitative research is efficient for the study but may pose negligible limitations to the overall result. For instance, the data collected might be a result of subjectivity. This is because of the qualitative design, where researchers analyse and interpret data for certain patterns and reasoning. At times, a researcher might decide what is important, thus affecting the overall result. Also, the sample size is too limited for effective generalizability. Conclusive and deductive reasoning will use the results to generalize artificial intelligence hindrances, which might not be the exact situation. These are, however, manageable, and negligible limitations as the advantages of the study method outweigh the disadvantages.
References:
Aarstad, A., & Saidl, M. Barriers to Adopting AI Technology in SMEs.
Alsheibani, S. A., Cheung, D., & Messom, D. (2019). Factors inhibiting the adoption of artificial intelligence at organizational-level: A preliminary investigation.
Ghobakhloo, M., & Ching, N. T. (2019). Adoption of digital technologies of smart manufacturing in SMEs. Journal of Industrial Information Integration, 16, 100107.
Hansen, E. B., & Bøgh, S. (2021). Artificial intelligence and internet of things in small and medium-sized enterprises: A survey. Journal of Manufacturing Systems, 58, 362-372.
Najib, M., & Fahma, F. (2020). Investigating the adoption of digital payment system through an extended technology acceptance model: An insight from the Indonesian small and medium enterprises. International Journal on Advanced Science, Engineering and Information Technology, 10(4), 1702-1708.
Puddephatt, A. J. (2017). George Herbert Mead. In The interactionist imagination (pp. 95-119). Palgrave Macmillan, London.
Radhakrishnan, J., & Chattopadhyay, M. (2020, December). Determinants and Barriers of Artificial Intelligence Adoption–A Literature Review. In International Working Conference on Transfer and Diffusion of IT (pp. 89-99). Springer, Cham.
Stentoft, J., Jensen, K. W., Philipsen, K., & Haug, A. (2019, January). Drivers and barriers for Industry 4.0 readiness and practice: a SME perspective with empirical evidence. In Proceedings of the 52nd Hawaii International Conference on System Sciences.[supanova_question]
The Final Paper must be submitted to Canvas so DO NOT PLAGIARIZE.
Writing Assignment Help The Final Paper must be submitted to Canvas so DO NOT PLAGIARIZE.
Final Paper is a 3 to 4 page paper explaining what you learned in this course. Describe 3 interesting concepts you have learned about culture and dance. You must including 3 references from 3 different chapters in the textbook and cite them with (page #).
Writing requirements for the paper:
Write your paper in essay format. At leat 5 paragraphes.
*The Introduction should include your understading of culture and dance after having taken this course. State 3 interesting concepts that you have learned from reading the course material. (paragraph 1)
*Give a detailed descriptionof the first interesting concept referencing the page or pages where the information is found in the book. (paragraph 2)
*Give a detailed descriptionof the second interesting concept referencing the page or pages where the information is found in the book. (paragraph 3)
*Give a detailed descriptionof the third interesting concept referencing the page or pages where the information is found in the book. (paragraph 4)
*Conclude your paper with your discoveries and how you will apply what you have learned.
Papers must be MLA or APA format for citations and header (abstract in not needed =introduction paragraph serves as the abstract) 3 to 4 pages typed, double-spaced 12 font, standard margins. A title page must be included with the title of your paper, your name, then the professor’s name, and the course name, time of class or web course, semester taken. All quoted research information must be documented in MLA or APA format in the paper (author, (publication year) page #) and in the bibliography. Substantial points will be deducted for format errors.
Research Paper Rubric
The following deductions will be made for missing requirements. Every paper starts at 100 points.
Deductions
10 points – for each missing citation referenced from the textbook Dance and Cultural Diversity formatted MLA or APA using (O’Cadiz 2018, p#). Must have at least one from 3 different chapters in the textbook.
30 points –for no citations in paper (must reference the page number)
10 points – for no title page
5 points – for incomplete title page information (your name, class, semester, online/web, title of paper)
5 points – for each 1/2 page of text missing (3 pages of text required in addition to 1 source page and 1 title page, no deductions for more than 5 pages of text)
10 points- incomplete introduction
10 points – incomplete conclusion, state discoveries and profound insights
Deductions will be made for format, punctuation, grammar and spelling errors, and plagiarism.
All Written Assignments will be graded on the following criteria.
* Appropriately present and organize supporting information
* Choose information from reliable, relevant and valid sources
* Analyze, evaluate or interpret information critically for accuracy, appropriateness or sufficiency to pursue specific conclusion(s), argument(s) or solution(s)
* Clearly articulate the value, validity and relevance of argument(s) and conclusion(s),?and if applicable, acknowledge relevant personal perspective(s)
* Apply prior academic knowledge to a new context [supanova_question]
3 U1L1: Literary theory Excerpt from Harper Lee’s To Kill A Mockingbird
3
U1L1: Literary theory
Excerpt from Harper Lee’s To Kill A Mockingbird
PART ONE
When he was nearly thirteen, my brother Jem got his arm badly broken at the elbow. When it healed, and Jem’s fears of never being able to play football were assuaged, he was seldom self-conscious about his injury. His left arm was somewhat shorter than his right; when he stood or walked, the back of his hand was at right angles to his body, his thumb parallel to his thigh. He couldn’t have cared less, so long as he could pass and punt.
When enough years had gone by to enable us to look back on them, we sometimes discussed the events leading to his accident. I maintain that the Ewells started it all, but Jem, who was four years my senior, said it started long before that. He said it began the summer Dill came to us, when Dill first gave us the idea of making Boo Radley come out.
I said if he wanted to take a broad view of the thing, it really began with Andrew Jackson. If General Jackson hadn’t run the Creeks up the creek, Simon Finch would never have paddled up the Alabama, and where would we be if he hadn’t? We were far too old to settle an argument with a fist-fight, so we consulted Atticus. Our father said we were both right.
Being Southerners, it was a source of shame to some members of the family that we had no recorded ancestors on either side of the Battle of Hastings. All we had was Simon Finch, a fur-trapping apothecary from Cornwall whose piety was exceeded only by his stinginess. In England, Simon was irritated by the persecution of those who called themselves Methodists at the hands of their more liberal brethren, and as Simon called himself a Methodist, he worked his way across the Atlantic to Philadelphia, thence to Jamaica, thence to Mobile, and up the Saint Stephens. Mindful of John Wesley’s strictures on the use of many words in buying and selling, Simon made a pile practicing medicine, but in this pursuit he was unhappy lest he be tempted into doing what he knew was not for the glory of God, as the putting on of gold and costly apparel. So Simon, having forgotten his teacher’s dictum on the possession of human chattels, bought three slaves and with their aid established a homestead on the banks of the Alabama River some forty miles above Saint Stephens. He returned to Saint Stephens only once, to find a wife, and with her established a line that ran high to daughters. Simon lived to an impressive age and died rich.
It was customary for the men in the family to remain on Simon’s homestead, Finch’s Landing, and make their living from cotton. The place was self-sufficient: modest in comparison with the empires around it, the Landing nevertheless produced everything required to sustain life except ice, wheat flour, and articles of clothing, supplied by river-boats from Mobile.
Simon would have regarded with impotent fury the disturbance between the North and the South, as it left his descendants stripped of everything but their land, yet the tradition of living on the land remained unbroken until well into the twentieth century, when my father, Atticus Finch, went to Montgomery to read law, and his younger brother went to Boston to study medicine. Their sister Alexandra was the Finch who remained at the Landing: she married a taciturn man who spent most of his time lying in a hammock by the river wondering if his trot-lines were full.
When my father was admitted to the bar, he returned to Maycomb and began his practice. Maycomb, some twenty miles east of Finch’s Landing, was the county seat of Maycomb County. Atticus’s office in the courthouse contained little more than a hat rack, a spittoon, a checkerboard and an unsullied Code of Alabama. His first two clients were the last two persons hanged in the Maycomb County jail. Atticus had urged them to accept the state’s generosity in allowing them to plead Guilty to second-degree murder and escape with their lives, but they were Haverfords, in Maycomb County a name synonymous with jackass. The Haverfords had dispatched Maycomb’s leading blacksmith in a misunderstanding arising from the alleged wrongful detention of a mare, were imprudent enough to do it in the presence of three witnesses, and insisted that the-son-of-a-bitch-had-it-coming-to-him was a good enough defense for anybody. They persisted in pleading Not Guilty to first-degree murder, so there was nothing much Atticus could do for his clients except be present at their departure, an occasion that was probably the beginning of my father’s profound distaste for the practice of criminal law.
During his first five years in Maycomb, Atticus practiced economy more than anything; for several years thereafter he invested his earnings in his brother’s education. John Hale Finch was ten years younger than my father, and chose to study medicine at a time when cotton was not worth growing; but after getting Uncle Jack started, Atticus derived a reasonable income from the law. He liked Maycomb, he was Maycomb County born and bred; he knew his people, they knew him, and because of Simon Finch’s industry, Atticus was related by blood or marriage to nearly every family in the town.
Maycomb was an old town, but it was a tired old town when I first knew it. In rainy weather the streets turned to red slop; grass grew on the sidewalks, the courthouse sagged in the square. Somehow, it was hotter then: a black dog suffered on a summer’s day; bony mules hitched to Hoover carts flicked flies in the sweltering shade of the live oaks on the square. Men’s stiff collars wilted by nine in the morning. Ladies bathed before noon, after their three-o’clock naps, and by nightfall were like soft teacakes with frostings of sweat and sweet talcum.
People moved slowly then. They ambled across the square, shuffled in and out of the stores around it, took their time about everything. A day was twenty-four hours long but seemed longer. There was no hurry, for there was nowhere to go, nothing to buy and no money to buy it with, nothing to see outside the boundaries of Maycomb County. But it was a time of vague optimism for some of the people: Maycomb County had recently been told that it had nothing to fear but fear itself.
We lived on the main residential street in town–Atticus, Jem and I, plus Calpurnia our cook. Jem and I found our father satisfactory: he played with us, read to us, and treated us with courteous detachment.
Calpurnia was something else again. She was all angles and bones; she was nearsighted; she squinted; her hand was wide as a bed slat and twice as hard. She was always ordering me out of the kitchen, asking me why I couldn’t behave as well as Jem when she knew he was older, and calling me home when I wasn’t ready to come. Our battles were epic and one-sided. Calpurnia always won, mainly because Atticus always took her side. She had been with us ever since Jem was born, and I had felt her tyrannical presence as long as I could remember.
Our mother died when I was two, so I never felt her absence. She was a Graham from Montgomery; Atticus met her when he was first elected to the state legislature. He was middle-aged then, she was fifteen years his junior. Jem was the product of their first year of marriage; four years later I was born, and two years later our mother died from a sudden heart attack. They said it ran in her family. I did not miss her, but I think Jem did. He remembered her clearly, and sometimes in the middle of a game he would sigh at length, then go off and play by himself behind the car-house. When he was like that, I knew better than to bother him.
When I was almost six and Jem was nearly ten, our summertime boundaries (within calling distance of Calpurnia) were Mrs. Henry Lafayette Dubose’s house two doors to the north of us, and the Radley Place three doors to the south. We were never tempted to break them. The Radley Place was inhabited by an unknown entity the mere description of whom was enough to make us behave for days on end; Mrs. Dubose was plain hell.
That was the summer Dill came to us.
Early one morning as we were beginning our day’s play in the back yard, Jem and I heard something next door in Miss Rachel Haverford’s collard patch. We went to the wire fence to see if there was a puppy–Miss Rachel’s rat terrier was expecting–instead we found someone sitting looking at us. Sitting down, he wasn’t much higher than the collards. We stared at him until he spoke:
“Hey.”
“Hey yourself,” said Jem pleasantly.
“I’m Charles Baker Harris,” he said. “I can read.”
“So what?” I said.
“I just thought you’d like to know I can read. You got anything needs readin’ I can do it. . . .”
“How old are you,” asked Jem, “four-and-a-half?”
“Goin’ on seven.”
“Shoot no wonder, then,” said Jem, jerking his thumb at me. “Scout yonder’s been readin’ ever since she was born, and she ain’t even started to school yet. You look right puny for goin’ on seven.”
“I’m little but I’m old,” he said.
Jem brushed his hair back to get a better look. “Why don’t you come over, Charles Baker Harris?” he said. “Lord, what a name.”
“‘s not any funnier’n yours. Aunt Rachel says your name’s Jeremy Atticus Finch.”
Jem scowled. “I’m big enough to fit mine,” he said. “Your name’s longer’n you are. Bet it’s a foot longer.”
“Folks call me Dill,” said Dill, struggling under the fence.[supanova_question]
1 Surname 9 Student’s Name Professor’s Name Course Date Marketing Plan Company
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Marketing Plan
Company Profile
The company name is Dr Pepper Snapple Group (DPSG).
It is a beverage industry
Its headquarter is located in Plano, Texas USA.
The company was originally founded in 1885.
The company currently employs approximately 27, 000 workers
The annual revenue estimate is 11 billion dollars
The company’s primary products include RC Cola, Dr Pepper Snapple, 7 Up, A & W, Sunkist, Schweppes, Big Red, Canada Dry, Vernors, Mott’s, Nehi, Hawaiian Punch, Squirt, and other beverages.
The majority of Dr Pepper’s targeted customers are the youths within the age bracket of 18-29 years old. Research shows that the age group forms the heavy consumers of the company’s products.
The primary distribution channels for the company’s products are the company-owned bottlers and distributers across their market segments and niches. Other distributing channels include the associate licensed bottlers and distributers such as Pepsi and Coca-Cola bottlers.
The company’s key competitors include other soft drink manufacturers and sellers like PepsiCo, Red Bull, and Coca-Cola Companies.
The link to Dr. Pepper’s website is https://www.drpepper.com.
The link to Yahoo Finance is https://finance.yahoo.com.
Market Segmentation and Targeting
The main problem that Dr Pepper’s products solve in the market is ensuring maximum satisfaction of the diverse tastes and preferences for soft drinks globally among their target customers.
The company has over 21 percent market share globally for soft drinks. It regularly researches customers’ opinions from different market segments globally and modified its products to meet their expectations sufficiently. For example, the company introduced the Hot Dr. Pepper drink to serve the customers warmth during the cold winters (Dorfman et al., 23). The company’s potential customers are the youthful generations who have developed an intense taste for Dr Pepper’s soft drinks. As a result, the company’s total market is geared towards providing soft drinks that match their customers’ tastes and preferences. Diversification of the market has been one way of meeting the demands in the respective regions globally.
The key business segments within Dr Pepper’s broader market include Latin America Beverages, Packaged Beverages, and Beverage Concentrates.
The three segments operate as follows; Beverage Concentrates segment runs the major brand business section that comprises sales and manufacture of beverages throughout Canada and America. The specific leading brands involved within the segment include Canada Dry, Dr Pepper, Schweppes, Crush, Sun Drop, Sunkist soda, various forms of Hawaiian Punch concentrates, and RC Cola. On the other hand, Packaged Beverages segment runs brand sections that comprise the distribution and manufacturing business. It, therefore, manufactures and distributes packaged beverages and related products that include individual brands, specific private label brands, and third-party brands. It majorly operates within the USA and Canada. Lastly, Latin America beverages run its brands, manufactures, and distribute company’s products such as bottled water, carbonated mineral water, and vegetable juices throughout Latin America.
The marketing plan majorly focuses on the Beverage Concentrates segment. The segment operates the company’s core brands, thereby contributing significantly to the overall profitability of the business. The majority of the company’s target customers get served through the segment globally. The segment is responsible for the overall growth and profitability of the business (Dorfman et al., 25). Its manufacturing and distribution functions are geared towards establishing a chain of customers worldwide. It generates much profit compared to other segments and maintains the business’s functioning.
Situation and Company Analysis:
Economic environment
The majority of Dr Pepper’s product consumers are unemployed or whose income rates are comparatively low, especially in developing nations. Economic pressures to balance luxurious items like refreshers and afford basic needs, high-interest rates on consumables in some countries, and heavy taxation have reduced their purchasing power (Patrick, 3). The countries have different economic statuses; some are recovering, others are undergoing a recession, while the rest are prosperous in growth. For example, sales in America and Canada are better than recovering and collapsed economies (Zander, 2).
Technical environment
The modern technological advancement has moved the company to upgrade its products. Consumers have become vigilant on new product upgrades and have enabled the company to expand its production. New production technologies adopted among competitors have pushed the company to find new knowledge in production to fairly compete in the market (Dorfman et al., 21).
Industry Environment
Beverage industry has been one of the most rapidly growing industries globally and has opened the door to more entrants. Emerging trends like intensified focus on wellness and health, rise in luxury and convenience, increased competition, and sustainable production are of great interest (Zander, 7). The threat of substitute products like those of PepsiCo and Coca-Cola soft drinks has challenged Dr Pepper’s operation in the past and brought lots of competition in the beverage industry (Patrick, 5). New practices like promoting consumer health and safety have equally challenged Dr Pepper to upgrade his production.
Competitor Environment
Dr Pepper’s immediate competitors include Coca-Cola, Red Bull, and PepsiCo, which are equally renowned producers of soft drinks. Coca-Cola has been a popular seller worldwide and has been challenging in the industry. It enjoys large profit margins compared to Dr Pepper and other competitors. PepsiCo and Red Bull have fairly competed with Dr Pepper in revenue accrual and profitability with slight differences. The beverage industry has constantly been growing and supportive of the companies. Dr Pepper’s advantage over consumers stems from its good reputation and high product quality the most youths like.
Political Environment
Dr Pepper operates in countries with different political climates. However, significant regions of operation like the USA and Canada enjoy a stable political environment. Limited trans-border tariffs and duties apply to most commercial transactions (Dorfman et al., 18). The company has, however, diversified the systematic political risks in various countries.
SWOT Analysis
Strengths: The key strengths of Dr Pepper include its excellent reputation and strong brand recognition. This has enabled the company to compete favorably, attract more customers, and gather more profits. Secondly is a broad and diverse product mix (Umar, 7). The company has made significant milestones to produce a wide product range that satisfies most customers’ tastes and preferences. Thirdly is winning major bottling contracts for popular beverage dealers, including Davis Bottling Co and American Bottling Co, among others (Patrick, 8).
Weaknesses: The Company’s weaknesses include multi-product lines that have made product positioning in the market problematic, hence the difficulty in competition. Secondly is the slow pace in technology adoption since the company is old and adjusting becomes a significant challenge. Lastly is the inability to control distribution channels and limited parent control over subsidiary operations.
Opportunities: The key opportunities include constant observance of a health product line that has promoted fair competition and entry into other nations like Malaysia, China, and India. Others are a heavy investment in network marketing and promotion that helps promote the popularity of the company and products among youths and global marketing through the acquisition of various business licenses.
Threats: Significant threats include poor distribution channels, insufficient market, and competitive pricing (Umar, 9).
Mission, Objectives, and Goals
Dr Pepper’s mission is “To be the best beverage company in the Americas.” The specific objectives are; to offer exemplary products and services that meet the customers’ expectations and achieve a fair, competitive edge against other beverage producers globally. The company, therefore, has set goals to increase its future market share by approximately 10 percent and enhance its distribution channels across all countries of influence to reach all customers with their products (Dorfman et al., 20).
Ethics and Social Responsibility: Current Status
The company has set specific goals to promote consumer health and wellness, environmental sustainability, ethical and workplace sourcing, and philanthropy.
Recommendations
The company should ensure the production of goods that meet the International Standards Certification, minimize wastes emission into the surrounding by incorporating environment safe technology, and ensure consumer health and safety becomes their priority.
Customer-Decision- Making Profile
Identifying the customer and problem
The majority of decision-makers are the youths who prefer taking soft drinks mostly to refresh and entertain themselves. They make buying decisions based on the quality and type of glass they desire. The wide range of products Dr Pepper offers tends to accommodate their varied tastes and preferences. The primary problem that Dr Pepper’s products help them solve is meeting diversified tastes for soft drinks, especially when attending different events and parties or during entertainment (Patrick, 4).
Factors Influencing Customer Decisions
Factors influencing customer decisions include geographic attributes, social and psychological features, and personal and demographic characteristics.
Geographic factors include the region or location of buyers. For example, American and Canadian youths buy intensively compared to India, China, and African countries.
Personal and demographic factor manifests when male youths buy more soft drinks compared to females due to their high tastes and preferences.
Social and psychological factors include observable trends such as youths from high-class families purchasing more soft drinks than less advantaged cohorts (Dorfman et al., 26).
Reaching the customer
Two main marketing strategies can sufficiently meet the customers, namely, market diversification and market penetration strategy. The two strategies will help supply the individual segments with their specific needs and maintain existing customers against competitive pressures (Zander, 9). Besides, they help enhance customers’ loyalty and create solid and lasting relationships.
Positioning and Differentiation
Competitor Advantages
The competitive advantages of Dr Pepper lie in the provision of high-quality products, a strong reputation, and enhanced ethics and social responsibility. This has enabled it to perform better than PepsiCo and Coca-Cola in terms of increased volume share.
Market Niche and Positioning Strategy
The company’s anticipated market niche is providing carbonated soft drinks to the youthful generation in the global market. Therefore, the company should think of approaching the market through quality enhancement and offering luxurious products considering the shifting tastes and preferences of the youths (Patrick, 7).
Positioning statement
Dr Pepper is the only beverage industry that offers the best quality soft drinks because of new technology adoption in production and expansion of customers’ choice for goods.
Repositioning Considerations
The company can also begin approaching the niche through product reviews to accommodate buyers with low purchasing power (Patrick, 5).
Works Cited
Dorfman, L., Cheyne, A., Friedman, L., Wadud, A., Gotlieb, M. (2012). Soda and Tobacco Industry Corporate Social Responsibility Campaigns: How Do They Compare? PLoS 9(6): e1001241.doi:10.1371/journal.pmed.10011241, p 1-30
Patrick, F. (2020). Dr Pepper Company. Handbook of Texas, p.1-20 https://www.tshaonline,org
Umar, F. (2019). Dr Pepper SWOT Analysis, p 5-10
Zander, H. (2018). Keurig Dr Pepper Inc PESTLE Analysis, p.1-10[supanova_question]