The 4th Industrial Revolution
The 4th Industrial Revolution
Towards a sustainable Customer Experience in the Agribusiness retail industry: The 4th Industrial Revolution, it’s influence on digital marketing strategies & customer buying behavior in South Africa
Abstract
The 4th industrial revolution has seen a rapid change in technology. The technology is changing how everything is done. The agribusiness sector has not been left behind, and the technology is influencing how the marketing of agricultural products are commercialized and customer buying behavior. This research has been prepared to find out how technology in the 4th industrial revolution is influencing digital marketing strategies and customer behavior in achieving sustainability in customer experience in the agribusiness sector. The paper will utilize both qualitative and quantitative research design. A descriptive research plan will guide the research. The main objective of the study is to determine the influence of determining of the fourth industrial revolution on digital marketing strategy and customer buying behavior. The specific objectives include; determining the impact of big data on digital marketing strategies, to determining the influence of social media on marketing strategies, to determine the influence of machine learning and Robotics on the digital marketing strategy of agribusiness firms in South Africa and finally, the impact of technology on perception, needs, motives, and attitude of the consumer. The research will use both qualitative and quantitative research methods. The target population for the research is consumers and agribusiness firms in South Africa. The research will use a sample of 500 consumers and 100 agribusiness retailers. Both primary and secondary data will be collected. Data collection will be done through the use of questionnaires and interviews. The data collected will be analyzed using SPSS to determine how the correlation of different variables. The analysis will be done using descriptive analysis, chi-square test, and narration.
Keywords: Sustainable customer-experience, agribusiness, marketing, strategy, customer, behavior, Robotics, and machine learning
Table of Content
2.0 Statement of the Problem.. 4
3.1 Main Research Objective. 5
4.3 Relationship Between Variables. 8
5.1 Research Design and Plan. 8
5.3 Data Collection instruments. 10
5.4 Data analysis procedure. 10
6.0 Contribution of the study. 11
1.0 Introduction
The world is experiencing rapid changes in technology, and everyone is talking about the fourth industrial revolution. Internet of things, artificial intelligence, machine learning and robotic, and process automation have all arrived. According to Attaran (2004), most firms put consideration on the best way of interacting with customers. The transformation in the digital industry is setting customers as the number one priority for businesses. Different firms are putting these technologies into consideration and experimenting with them to meet the needs of the customer.
According to Reardon et al. (2019), the agricultural sector in South Africa saw an increase in price received by farmers by 4.3% in 2019. There is an increasing population, which is driving demand for agricultural products in South Africa. The staple food in South Africa is maize and is consumed either in its direct form or as a bread, cornmeal, and sweeteners. Wheat is also another staple food, but it is mostly imported as it is expensive to produce wheat in South Africa. Fruits are also consumed, and the majority of fruits consumed include pears, mangoes peaches, plums, and avocados, to name but a few. Some of the vegetables that are highly demanded include pumpkins, lettuce, tomatoes, and chicory
According to Deloitte (2019), advancement in technology is changing how retailers interact with their customers. Some of how technology is used include; understanding the different market segments. The move is essential as it gives insight into the best strategic directions that can be taken by retailers. Technology is also helping in containing costs. Containing cost is essential if the retailer wants to have a competitive advantage. Technology is also being used to in creating value. Value creation is a significant factor in determining purchasing decisions. Value creation is critical in giving different product differentiation, which is essential for competitive advantage. Additionally, technology is essential in increasing the customer experience. Features such a platform for collecting feedback from customers is vital if it to r
According to Makhitha et al. (2019), advances in technology have changed how consumers do their shopping and generally shopping behavior. From the beginning of 2017 to the end of 2018 saw a dramatic increase in online shopping. Different attributes affect consumer behavior. Online shopping is gaining momentum in South Africa, and it has become a critical topic for researchers. The research proposal is aimed at determining how the fourth industrial revolution is influencing digital marketing strategies and customer buying behaviors. The research wants to establish how the fourth industrial revolution is moving towards achieving sustainable customer experience in the Agribusiness retail industry. The study will use questionnaires and interviews to collect data for various variables. The research is essential because it will help highlight the association between variables
2.0 Statement of the Problem
Big data, artificial intelligence, among other technologies, are revolutionizing how business is done. According to PwC (n.d.), the revolution on agribusiness entails critical shifts on how innovative technology is implemented and utilized to meet the demand for food and sustainably address food security globally. The fourth industrial revolution will play a critical role in agribusiness as the population increases in light of climate change. Agribusiness is going high-tech utilizing drones meant to gather data, and artificial intelligence to increase the precision of agriculture and increase efficiency and effectiveness to attain high profitability.
According to Lybbert and Sumner (2012), it is essential to note that even though there are advancements in technology, farmers still experience challenges in accessing some of these technologies in South Africa. Africa as a whole is still lagging and jas not gained a competitive advantage in the agricultural sector when compared to other countries. Technology is meant to help agribusiness achieve growth, create and strengthen relationships with its customers, increase efficiency, and allow businesses to learn more about each other. Technologies such as big data can help the business get insights into customers’ behavior and thus shape marketing strategies.
On the other hand, consumers are increasingly using technology. More and more consumers are now using technology to make purchasing decisions. The eCommerce platforms are changing, and consumers can access more information concerning different products. The research, therefore, wants to find out how agribusiness in South Africa is achieving sustainable customer experience through the use of the fourth industrial revolution technology. The study seeks to determine how technology is influencing marketing strategies of agribusiness firms and the buying behavior of consumers in South Africa to achieve sustainability (Maumbe and Okello, 2013).
3.0 Research objectives
3.1 Main Research Objective
The main objective of the research is to determine the 4th Industrial revolution, it’s influence on digital marketing strategies, and customer buying behavior in South Africa.
3.2 Specific Objectives
The specific objectives of this research include;
- The influence of big data on the digital marketing strategy of agribusiness firms in South Africa
- The impact of artificial intelligence on the digital marketing strategy of agribusiness firms in South Africa
- The influence of social media on the digital marketing strategy of agribusiness firms in South Africa.
- The influence of machine learning and Robotics on the digital marketing strategy of agribusiness firms in South Africa
- The influence of e-commerce on customer buying behavior in South Africa
- The impact of social media on buying behavior of customers in South Africa
4.0 Literature Review
4.1 Theoretical Paradigm
The theory of Structuration
Anthony Giddens developed this theory in 1984 (Bryant and Jary, 2014). Structuration is a social theory that covers reproduction and creation in social systems. The theory analyzes both agents and structures but does not give primacy to either of the two. In structuration theory, neither macro nor microanalysis is sufficient alone. Structuration theory examines hermeneutics, phenomenology, and social practice at the inseparable intersection of agents and structures. According to Corman (2008), Structuration theory proposes that communication, when integrated within the social system, is not only a matter of social structure or individual action but also a joint product of the social activity, including communication as an outcome of Structuration, and reproduction and production in social interaction. The theory of Structuration can be considered as one of the most influential perspectives in the communication discipline.
The theory of Actor-network
The theory was developed by Michel Callon and Bruno Latour in 1980 (Greenhalgh and Stones, 2010). The theory proposes that nothing is existing outside a relationship. The theory further suggests that in social situations, all factors are on the same level. On social forces determines how and what participants in a network interact. The theory suggests that ideas, objects, and processes, among other factors, are essential factors in creating a social network for human beings.
4.2 Research Construct
According to Hooker et al. (n.d.), many agribusinesses are increasingly adopting the internet for marketing and management. The internet and technology are proving to be a lifeline that determines the success and failure of a business. The use of technology can help a business gain more customers, increase its awareness in public promote its strategic position as well as increase its sales. According to GHD and AgThentic (2018), emerging technologies in agriculture are driving profitability and sustainability. These technologies also affect consumer choices and how they are engaged with agribusiness firms.
According to GHD and AgThentic (2018), consumers’ perception has an impact on the adoption of technologies used in agribusiness. According to Gandhi (2014), there is increasing competition in the agricultural sector, and the need to be profitable drives farmers to scale their operations to be optimum and achieve viability and competitive advantage. Wekeza and Sibanda (2019) researched Factors Influencing Consumer Purchase Intentions of Organically Grown Products in Shelly Centre, Port Shepstone, South Africa. The research design utilized by the research was descriptive cross-sectional, and 150 consumers were selected for the study using systematic random sampling. The research found that safe, high-quality products and environmentally friendly products were some of the drivers why consumers preferred these products. However, a survey by Deloitte (2016) revealed that while taste, convenience, and price have been traditional factors influencing a customer purchase decision, the decisions are shifting to health and wellness, social impact, safety, transparency, experience. These factors are directly affected by technology. A factor such as transparency is only possible if the information is easily accessible.
4.3 Relationship Between Variables
The independent variables in this research include big data, artificial intelligence, Machine learning and Robotics, e-commerce, and social media. The dependent variables are marketing strategies and consumer behaviors. Technology is continuously impacting the human aspect. For instance, e-commerce is changing how purchase decisions are made. Companies such as Amazon are changing how customers make their purchase decisions. For example, artificial intelligence is increasingly being adopted in developing countries found in Asia, such as India. Artificial intelligence is increasingly becoming important in how agricultural products are m, marketed, and sold.
Big Data is also shaping marketing strategy in other countries. Big data is essential in that it can help farmers to predict rainfall patterns, the requirement on fertilizer, water cycles, among other conditions. Bi data is, therefore, crucial in making smart decisions to increase profitability and better commercialization agribusiness. Also, machine learning and Robotics is crucial in marketing strategy because it the systems can learn the different trends in the market and adapt these trends to make future prediction and the best strategies that will increase profitability. Machine learning will enable these robots to collect data necessary in the application of big data and making strategies to increase market share.
5.0 Research Methodology
5.1 Research Design and Plan
According to Salkind (2010), research design can be referred to as the strategy picked by the researcher in integrating different components of the research logically and coherently to ensure that the study effectively addresses the research problem. The research problem includes a blueprint for the collection of data, measurement, and data analysis. The paper will use both qualitative and quantitative research design. The qualitative research design is vital for this research because it will help answer the question of why consumer behavior. Qualitative is very important in analyzing consumer behavior through interviews and questionnaires. The qualitative research design will help in understanding how the different aspects of the fourth industrial revolution are impacting consumer choice. It is vital in explaining the reason why consumers choose certain products (Maxwell, 2012)
A quantitative research design will also be employed in this study. Quantitative research design is essential in demonstrating the implementation of strategy and choice between the plan in light of new technology and data. The research design is necessary for explaining the choice of marketing and how successful the strategies have been when implemented using new technologies (Dimitrov, 2008).
The research will utilize a descriptive research plan. According to Nassaji (2015), the descriptive research plan is essential in describing the different phenomena of the population. It will help answer the questions of why, when, how, who and which. Descriptive research is essential in understanding the research problem, such as the current state of the fourth industrial revolution in South Africa.
5.2 Population and Sample
The target population for this study is people and firms living and operating in South Africa. The research wants to determine how the industrial revolution is influencing digital marketing strategies and consumer purchase decisions. For digital marketing strategy, the study is targeting firms and businesses doing agribusiness while consumers will form the population for purchase decisions (Moore, 2016). According to Cochran (2007), sampling refers to a technique used to select respondents for the study. Sampling is essential because it helps reduce the cost of collecting data. Both probability and non-probability sampling will be used.
The research will sample 100 businesses that engage in agribusiness in Pretoria. The business will be sampled using both stratified and random sampling. The businesses will be stratified according to sizes, and then samples picked from each sample. Conducting stratified sampling will ensure that no unique characteristic is left out, while random sampling will ensure that each element in the stratum has an equal chance of being picked. On the other hand, sampling on consumers will also be done using random sampling. Random sampling is considered appropriate because of the large number of respondents (Moore, 2016).
5.3 Validity and Reliability
According to Golafshani (2003), validity refers to the extent to which an instrument in research measures what it purports to measure. Reliability on the hand refers to to the degree in which measurements taken by the research tools are consistent. Validity is concerned with how meaningful and accurate the inferences based on the research are. The validity of the research will be examined using three dimensions, including; construct, content, and criterion. Additionally, the research will rely on developed instruments that have been used in other similar studies and concepts that have been generated from appropriate literature. The researcher will utilize Cronbach’s Alpha to determine and enhance the reliability of research instruments.
5.4 Data Collection instruments
Primary and secondary data will be used in the research. Questionnaires and interviews will be used to collect primary data. Questionnaires will be used when collecting data from consumers. Questionnaires are appropriate because they are a relatively cheap and efficient way of collecting data. Questionnaires are also vital because they can be emailed to the respondents. Questionnaires will be both open-ended and close-ended, and this is important in collecting both quantitative and qualitative data (Bolarinwa, 2015).
On the other hand, data from businesses that engage in agribusiness will be collected using interviews and questionnaires. According to Aksu (2009), interviews are open-ended and give an in-depth analysis of the different variables. Data on strategy is required an in-depth analysis, and that is the reason for the use of interviews. Some of the data concerning marketing strategy will also be collected using questionnaires. Secondary data will be collected from books and journals.
5.5 Data analysis procedure
The researcher will collect both qualitative and quantitive data. Qualitative data will be analyzed using exploratory research and data analysis. Qualitative data from interviews and questionnaires will be analyzed using narrative analysis. Quantitative data will first be validated to ensure that they meet pre-set standards. The data will then be edited. Editing helps in reducing errors in the data collected. Data editing helps in ensuring that they can be analyzed without problems. The next phase will be coding the data. Data coding is critical to ensure that collected data can be grouped and assigned values. Quantitative data will then be analyzed using descriptive statistics, inferential statistics, and Chi-square tests. Descriptive statistics is essential in measuring frequency in the data, measuring central tendency in the data, measure the position of the data and dispersion. Inferential statistics will help in testing the hypothesis and estimating different parameters of the study. The chi-square test will be used to measure the relationship between different variables.
6.0 Contribution of the study
This research will be of importance since it will contribute to the understanding of how the fourth industrial revolution is impacting the agribusiness digital marketing strategy. With the coming of technology and its influence on every aspect of human life, it is crucial to understand how big data, artificial intelligence social media, and e-commerce is affecting the strategic marketing on the digital platforms. The research will help shape the future application of these technologies in agribusiness as South Africa tries to gain a competitive advantage as well as meeting customer needs. The study is also vital in understanding how these technologies are influencing consumer purchase behavior. The research will help in ensuring that the technology can help achieve sustainability in agribusiness through meeting customer needs and the use of the best strategies.
The research is also essential in the academic world as it will highlight the importance of different theories and their application to human life. The research will allow further study in areas that may not be covered as it tries to highlight the effect of fourth industrial revolutions. The research is also essential to the South African government in shaping policies that are meant to see the growth of the economy. The government can give incentives and education on how best to do agribusiness through commercialization and increasing profitability. The policies are vital in growing the economy of the country.
References
Attaran, M., 2004. Exploring the relationship between information technology and business process reengineering. Information & management, 41(5), pp.585-596.
Aksu, H.H., 2009. Questionnaries and Interviews in Educational Researches. Journal of Graduate School of Social Sciences, 13(1).
Bolarinwa, O.A., 2015. Principles and methods of validity and reliability testing of questionnaires used in social and health science researches. Nigerian Postgraduate Medical Journal, 22(4), p.195.
Bryant, C. and Jary, D. eds., 2014. Giddens’ theory of Structuration: A critical appreciation. Routledge.
Cochran, W.G., 2007. Sampling techniques. John Wiley & Sons.
Corman, R. S., (2008). Structuration Theory https://doi.org/10.1002/9781405186407.wbiecs111
Deloitte., (2016). The changing drivers that influence consumer behaviour https://www2.deloitte.com/za/en/footerlinks/pressreleasespage/the-changing-drivers-that-influence-consumer-behavior.html
Deloitte., (2019). Consumer Sentiment in Retail: Insights for South Africa https://www2.deloitte.com/content/dam/Deloitte/za/Documents/Consumer_Industrial_Products/ZA-Deloitte-Consumer-sentiment-in-Retail-Insights-for-South-Africa-2019-2.pdf
Dimitrov, D.M., 2008. Quantitative research in education. New York, NY: Whittier.
Gandhi, P. V., (2014). Growth and Transformation of the Agribusiness Sector: Drivers, Models, and Challenges https://ageconsearch.umn.edu/record/206364/files/Gandhi69_1.pdf
GHD & AgThentic., (2018). Emerging technologies in agriculture: Consumer perceptions around emerging Agtech https://www.agrifutures.com.au/wp-content/uploads/2019/01/18-048.pdf
Golafshani, N., (2003). Understanding reliability and validity in qualitative research. The qualitative report, 8(4), pp.597-607.
Greenhalgh, T. and Stones, R., 2010. Theorizing big IT programmes in healthcare: strong structuration theory meets actor-network theory. Social science & medicine, 70(9), pp.1285-1294.
Hooker, N. H., Heilig, J., & Ernst, S., (n.d.). What is Unique About E-Agribusiness? https://pdfs.semanticscholar.org/c21f/9d05364f3117e4c2119c83266d317afa0148.pdf
Lybbert, T.J. and Sumner, D.A., 2012. Agricultural technologies for climate change in developing countries: Policy options for innovation and technology diffusion. Food Policy, 37(1), pp.114-123.
Makhitha, K., & Scheers, L., & Mogashoa, C. (2019). Which consumer attributes influence South African consumers to shop online. Journal of Business & Retail Management Research. 13. 10.24052/JBRMR/V13IS04/ART-29. https://www.researchgate.net/publication/334276117_Which_consumer_attributes_influence_South_African_consumers_to_shop_online
Maumbe, B.M. and Okello, J.J., 2013. Uses of Information and Communication Technology (ICT) in agriculture and rural development in sub-Saharan Africa: Experiences from South Africa and Kenya. In Technology, Sustainability, and Rural Development in Africa (pp. 113-134). IGI Global.
Maxwell, J.A., 2012. Qualitative research design: An interactive approach (Vol. 41). Sage publications.
Moore, F., (2016). Research Design Plans. 10.13140/RG.2.2.10120.01281. https://www.researchgate.net/publication/310572209_Research_Design_Plans
Nassaji, H., 2015. Qualitative and descriptive research: Data type versus data analysis.
PwC., (n.d.). Technology set to boost production in agribusiness https://www.pwc.co.za/en/press-room/tech-innovation-agribusiness.html
Reardon, T., Echeverria, R., Berdegué, J., Minten, B., Liverpool-Tasie, S., Tschirley, D. and Zilberman, D., 2019. Rapid transformation of food systems in developing regions: highlighting the role of agricultural research & innovations. Agricultural Systems, 172, pp.47-59.
Salkind, N.J. ed., 2010. Encyclopedia of research design (Vol. 1). Sage.
Wekeza, S. V., & Sibanda, M. (2019). Factors Influencing Consumer Purchase Intentions of Organically Grown Products in Shelly Centre, Port Shepstone, South Africa. International journal of environmental research and public health, 16(6), 956. https://doi.org/10.3390/ijerph16060956
