Executive Summary
The mining companies of today are like the taxi cab companies of yesterday: resistant to change yet with an understanding that the future for them will be different for them. Think artificial intelligence, automated decision making, and humanoid robots – unarguably the future, regardless of a company’s desire to resist.
But when it comes to technology innovations, mining companies tend to take a more than conservative approach. There are plenty of reasons why this is the case, which includes the industry remains profitable so why change, physically old technology adverse executives captain the industry, the barriers to entry are too high, the risks are too great if it is not broke why to fix it and the list goes on.
The vast majority of mining companies are considered to be mom-and-pop operations when compared to the large established mining companies with diversified mineral portfolios. Due to the nature of the industry as being fragmented, which often yields thin profits, some companies have not been able to adopt technology as they should have.
It is starting to change, however slowly and not universally. Most of the noticeable change within the industry have been pioneered by the major mining firms. Not surprisingly the majority of technological advances within the industry are nothing more than the incorporation of existing and proven technology developed elsewhere.
Operators are now operating equipment in special operating rooms sometimes thousands of miles away via an internet connection instead of being in an on-site. The software is assisting in deciding when and where to mine. For instance, mining companies can make data-driven decisions. Data can help them locate mineral veins, streamline operations, and determine risks for their workers. Furthermore, the use of technology in the form of autonomous trucks, automated haulage systems, and sensor-based sorting technology can change the way mining would be done in the future. Still today, from a technology standpoint the mining industry has not been viewed as catching up with the times. The industry is now in a position where existing business models may not prove profitable in the future.
Agreeing to the fact that mining will look vastly different in the future with the deployment of technology, there is a lack of understanding of what then would be the structure of a typical mining company. Failures in industries where business models remained stagnant, and as a consequence, organizations became insolvent, are often explained by unsuccessful business models. The music recording industry, the taxi industry, and the cable television industry are all good examples of industries drastically changed by technology much to the detriment of major corporations resistant to change.
What skills or specializations will a mining company need to employ to be profitable? As an example, Rio Tinto declared back in 2017 than 50% of their truck fleet will be autonomous by 2019 and that the retrofit program will assist the iron ore business in delivering an additional $500 million of free cash flow annually from 2021. Does this not indicate that a valuable competency for a mining company to have in the future is the automation of machinery? What other competencies should mining companies have? What competency do they currently have that will be obsolete in the future?
Addressing these questions, this research will explore the probable core competencies of future mining entities and the impact on the mining industry when corporations shift to the proposed new core competencies.
Even though the future of mining has attracted attention from scholars and practitioners alike, little research has been conducted on future business models for the mining industry. Moreover, little weight has been given to the future business models of mining companies both in research and practice. The field of business model research within the mining industry is highly fragmented, and its depth as an academic research stream has been sparse. The business model concept is studied within many academic fields, building on ideas from, e.g., strategic management and entrepreneurship (Morrisa, Schindehutte, & Allen, 2005), value chains and systems (Amit & Zott, 2001), strategic positioning, resource-based theory (Amit & Zott, 2001), strategic networks (Amit & Zott, 2001), and cooperative strategies (Amit & Zott, 2001). The use of innovative processes, automation, and technology is drastically affecting the business model of mining companies. The changing technologies are causing business models to change as well to better adapt to it (Becker, 2017). However, research conducted on business model change and innovation within the mining industry does not have a solid theoretical foundation and has yet to receive widespread attention. There is, surprisingly, a great deal of evidence and anticipation that the mining industry is on the cusp of great change and disruption.
This research could enrich the discussion of many aspects of human civilization due to the fundamental necessity of mineral extraction in today’s world. For example, if the business model of mining companies is to operate without human assistance/intervention what will become of the hundreds of millions employed directly and indirectly by the mining industry? If a required competency of a mining company in the future is artificial intelligence, should governments around the world encourage education in data science and technology? If millions of people are physically moving less, as is currently the case with lots of jobs in the mining industry, are health care systems set up to handle the consequences? These topics along with national policy, international economics, capital markets, technology, human capital and just a few to be enriched with a greater understanding of what the future mining corporation will look alike.
The empirical setting of the study will be based on two research projects: probable core competencies of future mining entities and the impact on the mining industry when corporations shift to the identified core competencies. Using a variety of methods, such as interviews, observation, and Delphi questionnaires, data will be gathered via case studies.
This research will contribute to mining strategy and business modeling research by introducing the probable core competencies of future mining entities and exploring the impact to the mining industry when corporations shift to the identified core competencies.
Introduction
The literature Review section has been structured as per the flow of research on the topic. The research on the mining industry and the changes that it is undergoing currently was the prime concept that was searched first. It led to the study of literature on the impact of these changes in the mining industry and how it is influencing the mining corporations. The Advancement in the ICT (Information, Communication and Technology) was the prime driver of the changes in the industry, which caused the research to look for literature on the influence of ICT on the mining industry. The review is structured mainly as per the research questions. The review first builds on the literature that is covered under the primary research question. It includes the area of the probable core competencies needed by the companies in the mining industry in the future to survive the changes and how it influences these companies. Extending from this, the literature on the secondary research questions is covered.
Background:
The future of mining is dynamic due to the likely changes. To achieve maximum benefits from the mining industry, it is necessary for the stakeholders (organizations, investors, suppliers, and customers) to be proactive in addressing the emerging challenges. There is an increasing human population worldwide, and this causes a rise in the demand for diverse mineral resources. Also, the current performance in the global economy is sufficient, increasing the disposable income to purchase the mineral products. The increasing production causes a rising depletion of mineral resources. Thus, there is the need to use emerging technology trends to develop appropriate solutions for the issues experienced by the contemporary mining entities. The discussion provides a critical analysis of key competencies that will be effective in facilitating the innovation and problem-solving capabilities of the entities in the future mining industry.
Research Objectives:
The objectives of the research are.
- To recognize the trends which influence the mining industry
- To examine the impact of the trends in the mining industry
- Identify the core competencies crucial for the future mining industry
- To examine if the adaptation of the core competencies would influence the performance of the mining companies.
Research Questions
The primary research question for the study is:
- What are the probable core competencies in the future mining industries?
- What are the likely impacts of the corporations?
The primary question is the main question that supports the main purpose of the research study. Thus, it investigates the new trends in the mining sector that aim at enhancing the performance of the organizations and achieving the diverse interests of all the stakeholders. Advancements and innovations in the Information and Communication Technology (ICT) sector are the driver of new trends in the mining industry. For example, the professionals working for mining companies can communicate effectively using the instant messaging platforms that are available online, on the social media, website, email, or mobile app platforms (Sivakumar, Kannan, & Murugesan, 2015). It is also important to examine the impact of the trends on the organizations that operate in the competitive mining sector. The trends aim at enhancing the organizational competencies. For example, automation in the mining sector improves the quality and quantity of the products and services. As a result, the customers get superior mineral products that have a high utility value. Also, the automation process limits labor requirements because the production activities are done by intelligent machines and systems like robots (Trudel, Nadeau, Zaras, & Deschamps, 2015). As a result, there are savings on labor costs, and this implies that the automation trend will enhance the revenue and profitability levels of the organization.
From the primary question, several secondary research questions can be generated. One secondary question is:
What is the desired core competencies in the future mining sector?
The skills, experience, and knowledge should enhance the performance of the mining organizations. Various online programs enhance the knowledge of mineral exploration.
The second research question is: What are the trends in the mining industry?
The trends illustrate the changes that are being adopted in the present mining sector to ensure the performance of the companies in the future. Some of the trends are innovation, globalization, Artificial Intelligence (AI), robotics, and project teams (Hardy, Heller, Faltyn, & Stefanaki, 2017). Innovation involves the adoption of new practices that improve the quality and quantities of the products and services offered by the mining companies for the benefit of the clients. AI is the use of computer systems to perform various company processes. Robotics enhances the automation processes, and thus the quality of products and services is enhanced. The projects allow the staff from different professional backgrounds to work together to achieve the goals and objectives of the mining entities. The third secondary question is:
What are the effects of the core competencies or trends in the performance of the mining corporations?
The core competencies should improve the performance of the companies operating in the future mining sector. For example, the innovation abilities and use of AI capabilities improve the exploration processes in remote locations. The fourth research question is:
Are the corporations in the mining sector ready to adopt the emerging core competencies?
There are various strategies that the entities can use to enhance the readiness for the mining environment (Zhironki, Tyulenev, Zhironkina, & Hellmer, 2016).
The significance of the Research:
The research is significant regarding its use by the mining companies to not only realize the significant trends which are influencing the mining industry, but to also identify the core competencies which would be needed by these companies to adapt to these changes. Furthermore, this study would help the mining companies to know if the core competencies influence the performance of the company in perspective of the adaptation of the new trends. The results of this study would be helpful for the mining industry to encourage automation and use of technology in their operations.
Review of the Literature
The literature review is structured as per the research flow that was conducted. The research started by looking for specific journals on the mining industry. It helped in the identification of the journals of Metallurgical and mining industry, International Journal of Mining Science and Technology, International Journal of Mineral Processing, Journal of Mining Science, Minerals Engineering, Inside Mining. The thorough study of these journals showed some interesting articles relevant on the study. Following that, the research on the mining industry and the changes that it is undergoing currently was the prime concept that was searched first. Search keys like the “impact of technology on mining industry”, mining industry and technology”, “automation in mining industry”, “future of mining industry” were used for the research on several search engines. It led to the study of literature on the impact of these changes in the mining industry and how it is influencing the mining corporations. The Advancement in the ICT was the prime driver of the changes in the industry, which caused the research to look for literature on the influence of ICT on the mining industry. The key words of “ICT impact on mining industry”, “ICT and mining” were used for searching. The review is structured mainly as per the research questions. Grey literature has been mostly used for the purpose of research. Grey literature is a really important source of information as these are mostly unique publications yielding more current information.
Trends Driving Changes in Mining Industry:
The mining sector has experienced highs and lows during the past decade. The present performance of the global mining sector is satisfactory in terms of revenues due to the strong prices of mineral products. However, the forecasts in the sector illustrate that the next decade will experience a vigorous and extensive change in the form of digitization, technology advancement, innovative processes, robotics, artificial intelligence, and data analytics (Lawrence & Davies, 2015) Evidently, mining companies have been using the evidence of the past best practices in the mining sector in developing successful strategies for the future business processes as not much changes has occurred in the mining industry in the past. However, this will not be very helpful in the coming future because of the nature of the changes coming in future years.
There is the widespread acceptance of digitalization in the current mining sectors due to the forecast benefit in performance enhancement. The value proposition of the mining industry is shifting towards effective utilization or data or information to enhance the production processes, minimize business expenses, enhance efficiency, and increase the safety levels in the mining sites. The ability to collect data, and process it appropriately to achieve the desirable standards, is a key competitive advantage in the mining sector of the economy (Lawrence & Davies, 2015). To realize the digitalization goals, the miners need to have a clear vision of the effect of the future digital mine on the key mining systems, the transfer of information, and the complementary back-office activities. After the data capture stage, the online analytics engage in optimizing the mining processes to achieve the interests of the internal and external organizational customers. There is an increasing usage of Internet technology that facilitates on-site and off-site data storage and processing facilities. The cloud infrastructure provided by IT companies like Amazon is effective in the off-site storage, processing, and retrieval of voluminous data (Lodhia & Hess, 2014). A good example of the data that is stored in the digital platform for ease of processing and retrieval is mineral exploration activities. Also, the financial statements are stored in the cloud infrastructure to enable the shareholders to monitor the returns on their investments.
Barriers to Innovation:
It is important to address the barriers to innovation that may exist in the present mining sector. Innovation is important in creating positive changes and introducing new technologies, which improve the performance of the mining companies. There are barriers and challenges to the innovation processes as the mine designs, and the systems of processing have not been altered in decades (Makinde, Ramatsetse, & Mpofu, 2015). The financial returns of the mining sector were adversely affected during the global financial crisis. Therefore, the disposable income of the individuals and organizational customers was insufficient, resulting in a reduction in the sales volumes and profitability of the mining organizations. Drawing from the experiences during the global financial crisis, the mining executives are cautious. They limit innovation and aim at achieving positive short-term returns that win the support of the investors (Sivakumar, Kannan, & Murugesan, 2015). But the company can only achieve the set long-term targets or vision if it implements new ideas and adopts innovative technologies in mining activities.
Future of Mining Industry:
The future of work will be different in the mining sector due to the effects of digitization. For example, repetitive tasks will be performed by robotic systems. As a result, a significant proportion of the workforce will be declared redundant. The declining demand for human labor implies that the organization will save on labor costs, resulting in a significant increase in the net revenues of the mining companies. Automation will enhance safety in the mining sites, due to the reduction in the number of employees in active employment (Makinde, Ramatsetse, & Mpofu, 2015). Also, the mining activities will be done by experts who use computer programs that direct all work activities. Artificial Intelligence systems will enhance the competencies of the knowledge workers, and thus they will develop goals and objectives that are in demand in the global mining sector. The systems will enable the knowledge workers to identify suitable exploration sites that are cost-effective to enhance the revenues of the organization. Integrated online communication is beneficial in supporting the mobile worker. They can be conducting exploration activities on-site while sending real-time data and information to other professionals in the branch or headquarters. The process of digital work scheduling improves the work processes and eliminates the issues of task duplication, obsolete duties and responsibilities, and excess workforce. Cyber security is necessary for protecting the data of the mining corporations (Sivakumar, Kannan, & Murugesan, 2015). Most of the data are sensitive as they illustrate the strategies that the companies will utilize to enhance the competitive advantage in the global mining sector.
For example, it is proposed that the adoption of IoT will enhance the communication process between the organizational stakeholders through the mobile apps or websites of the company. A customer can make inquiries on the availability of diamond jewelry products from a mineral processing company. The use of the conflict diamond traceability through the use of the block chain technology would enable the users to know that no diamonds have profited any parties who were faking it to pass conflict stones as genuine (Marr, 2018). Currently, De Beers, BHP Billiton, Rio Tinto, and Alrosa have these capabilities as these companies hold more than 65% of the market as diamond producers (Pisani, 2012). As a result, the level of customer satisfaction will improve resulting in high sales volumes and revenues. There is also the e-commerce process that enables the mining companies to sell products and services to the clients in the global business environment. One such example is that of using business-to-business e-commerce which can cause reduced expenses, streamline business processes, and help elevate the market leader in the mining organizations (S.K.Chaulya & G.M.Prasad, 2016). Thus, customers place orders via the website or mobile application of the mining company. After online payment, the company facilitates the shipping of the mining products to the customers within the stated period (Clifford, Perrons, Ali, & Grice, 2018). Thus, the key intention of the present study is to prove if the adoption of the core competencies in the mining sector will enhance the future productivity of mineral exploration, processing, and supply corporations.
IoT and IoE:
The mining trends are important as they enhance the effectiveness and efficiency of the mining processes. There is the trend of smart mining, which involves the integration of advanced ICT programs in the national and global mining operations. Adoption of ICT technologies is necessary for facilitating the competitive advantage of mining companies in the competitive business environment. For example, there is the digitization of the mining operations that is facilitated by the concept of the Internet of Things (IoT) and the Internet of Everything (IoE). IoT implies the application of online services in the performance of various transactions, for example, instant messaging through the website of the company. The IoE implies that all devices in the mining processes will have Internet capabilities, and they will possess the ability to communicate with each other, resulting in the enhancement of the AI applications (Silvestre 2014). The two applications mean that Internet technology will be applied on a large scale in the global mining sector. However, the utilization of the IoT and IoE technologies in the mining sector means that the developed economies like the United States, United Kingdom, Germany, Japan, and Russia will have a competitive advantage over the emerging and underdeveloped nations like India, South Sudan, North Korea, or Argentina. It is because the developed markets have sufficient advancement in Internet connection. Currently, there is the roll-out of the 5G internet infrastructure in the developing markets. 5G internet has high speed, and thus it is appropriate for the data-intensive mining activities (Clifford, Perrons, Ali, & Grice, 2018). The developed nations have a skilled workforce that is necessary for the integration of technology and innovations in mining companies. Also, the miners would need to contract the major technology companies like Microsoft Corporation and Apple, Inc. to provide innovative applications that are important in enhancing mining operations. Also, the National Space Agency (NASA) is an effective federal agency that is effective in satellite imaging and geospatial engineering, which are important processes in mineral exploration activities.
Robotics, Automation and Artificial Intelligence:
Automation is an important capability that enables enhancements in the operations of the mining companies. The significant automation strategy that is being adopted by the mining companies is the robotic system. Intelligent machines perform the duties that were traditionally performed by human professionals. The result is the replacement of human labor with intelligent systems. The robotic systems are affordable to maintain, and thus they enable the management of the mining corporations to record high revenues and profitability for the benefit of the shareholders. Rio Tinto, in Australia, is a leader in automation in the mining sector. The company uses robotic technology to enhance its transportation systems, within the iron ore mines. Software automation enhances the exploration, extraction, processing, quality control, and distribution systems in the mining activities.
AI improves mining activities, and it illustrates the desirable future trends in the sector. The technology streamlines various activities in the mining sector and also improves the safety levels in the mining work environment. AI makes effective use of the available data in the mining sector, which includes drilling surveys and geological data. The usability is experienced in making predictions on favorable sites for mining activities. It is also effective in providing recommendations on the sites that will have a general minimal impact on the natural environment and generate maximum returns for the benefit of the project sponsors and stakeholders. In the actual mining environment, AI is effective in the determination of the potential failure areas, and hence improves the repair mechanisms (National Research Council, 2015). Also, it is beneficial to determine the valuable ore during the process of fragmentation assessment.
Block Chain Technology:
Blockchain technology is an emerging trend that is facilitating the business or financial transactions of the mining corporations in the international commerce environment. It is also important in enhancing the supply chain management process of the mining corporation securely and effectively (Kalabin, 2015). The mineral end-users or customers are concerned with the entire process of producing the minerals. For example, the diamond mineral is precious, and the end-users have to ensure that the extraction and production processes adhere to the highest standards of quality and business ethics. In January 2018, De Beers communicated through a press release that it would apply blockchain technology to ensure that the diamond products that it produces and sells and registered to denote business ethics by upholding high standards of quality, environmental sustainability, and conflict-free production processes (Clifford, Perrons, Ali, & Grice, 2018). There are concerns that the diamond products from the Democratic Republic of Congo (DRC) are used to finance violence in the human society. Therefore, many customers have to be convinced that the diamond products that are being showcased for sale are not produced with the objective of financing terror or human violence activities. Also, the cobalt resources that are being mined in the DRC are tracked using blockchain technology to ensure that they are not sourced from the child labor environments. The technology is important in removing the intermediaries from the production and distribution business processes (Lodhia & Hess, 2014). As a result, the end-users have direct access and knowledge of the source of mineral products, with the intention of determining the legal, ethical, and environmental consciousness behind the production and sale of mineral products.
Drone Technology:
Drone technology is a major trend in the contemporary mining sector. The drones are self-piloting gadgets that are used to provide aerial perspectives in the mining environment. Drones improve the safety of the mining environment, especially during the site blasting activities. The drones ensure that there are no people near the sites earmarked for blasting to facilitate the mineral extraction processes (Ilankoon, et al., 2018). The drones are also used to monitor the effectiveness of the overhead cranes, which are used in lifting mineral ores from the mining site. The cranes are also important in facilitating the movement of the mining staff inside or outside the extraction areas. Drones are fitted with computer programs to produce 3D maps, to improve the mining exploration activities. The benefit of using the drones to provide aerial analysis of the mining data is affordable. It is cheaper to use the drones, that in the utilization of the airplanes (Makinde, Ramatsetse, & Mpofu, 2015). The drones are also faster, and they provide accrual measurements of the geography of the mining sites. In the underground mining sites, the drones are used to determine the safety levels and also provide data on the potential mineral deposit quantities, quality, and value, just before the commencement of the extraction activities.
3D Printing:
3D printing is a new technology that has applications in contemporary and future mining activities. The technology will minimize the extraction, processing, and distribution of minerals. It enhances the additive manufacturing process, instead of the utilization of traditional mineral production technologies. It, therefore, limits the production duration and thus saves time and resources of the organization. Additive manufacturing minimizes waste in the production environment because of high levels of energy efficiency and large-scale generation of custom designs (National Research Council, 2015). 3D printing also enables the small-scale operators to be profitable due to the cost-efficiency benefits.
Summary
The future of the mining industry will be lucrative if there is an effective exploration of the final frontiers. Currently, the mining activities in remote or inaccessible locations are challenging and expensive undertakings. However, the forecasts in the global mining sector illustrate the increasing desire to invest in the final frontiers due to the potential for high-value ores that can enhance the profitability of the mining businesses. The rate of mineral deposit depletion in the known mines is high. Also, the quality of the mineral-ore grades is declining because of the overexploitation of the sites. On the positive side, the global demand for the diverse mineral products is on a rising trend, implying that the value of the precious mineral commodities will continue to increase (Verma & Chaudhari, 2016). The risk in investing in the final frontier mineral sites is likely to generate high value returns for the benefit of the shareholders. Also, technological innovations have enhanced the know-how that enhances the effectiveness and performance of the final frontier mining areas. There is increasing environmental concern in the areas with the significant human population. To avoid conflicts or disagreements between the mining corporations and the local communities, it is important for the management to enhance investments in remote or inaccessible environments. The final frontier areas that are appropriate for mining activities include space, arctic and deep-sea locations (Silvestre, 2014). Developed economies like the United States and Russia have invested heavily in the Arctic mining projects. The first deep sea mining project is set to begin in 2018, led by the Canadian mineral exploration company Nautilus Minerals. In space, there are asteroid exploration projects that are scheduled to be performed in 2019, by the Deep Space Industries. The final frontiers provide access to the high-value mineral resources like rare earth and base metals. As the value of mineral resources increases, there are expectations that companies with sufficient capital and know-how can enhance investments in the final frontiers. The main problem with deep-sea mining efforts is the environmental concerns regarding pollution and the destruction of marine life. Space mining is increasing in prominence as it offers a viable strategy to address the issues of resource overexploitation on earth (Clifford, Perrons, Ali, & Grice, 2018). There is increasing government support for space exploration activities, as seen by the National Space Agency (NASA) efforts in mineral exploration in space.
Conclusion
The mining companies have been resistant to change due to the complexity as a result of the good business environment presently. Precious minerals attract high value in the global business environment. However, research evidence (Lawrence & Davies, 2015) illustrates embracing positive change, and innovation strategies will enhance the competitive advantages of the mining entities in the global business environment. Thus, the research explores the positive trends and the potential benefits that will enhance the future performance of mining corporations. The key driver of change and innovation in the mining sector is Internet technology. The IoE or IoT concepts imply that all activities in the mining sector will be facilitated by the online transmission and processing of data. There is the increasing penetration of the 5G internet, especially in the developed economies. As a result, the corporations can collect, process, store, and retrieve data and information about different aspects or processes in the mining environment.
The literature review has helped in realizing the major trends that are influencing the mining industry. These trends have the potential to influence the core competencies of the mining corporations and consequently affect their performance in the future. The review of the literature has helped in recognizing the relationship between the core competencies and the performance of the mining corporations. These core competencies will be used for researching its influence on the performance of the company.
Methodology
Methodology Concept & Approach:
Mixed research methodology is appropriate as qualitative and quantitative approaches to data collection, analysis, and presentation will be applicable. Qualitative research focuses on the experiences of the stakeholders in the mining sector on the adoption of the core competencies. Quantitative research illustrates the numerical analysis of the data on the impact of the potential core competencies on the future performance of the mining sector (Lawrence & Davies, 2015). The variables in the study are dependent and independent. The independent variable is the core competencies, which include technological innovation tends, capacity building, and resource availability in the future mining sector. The dependent variables are influenced by the implementation of the core competencies. They will include the performance of the mining industries in the future. The main hypothesis of the study is the adoption of the core competencies improves the performance of the organizations in the mining sector (Becker, 2017).
Interview and Questionnaire:
There are several important data collection techniques that enhance the research process. They aim at offering answers to the research questions to understand the relationship between the research variables. For the primary research, interviews will be used to collect data from 30 professionals who work in the current mining sector. The size of the sample is decided based on snowball sampling method contact. There are hundreds of professionals in this industry; even though one is tempted to interview a large sample of professionals, only the ones with key positions and from a variety of companies would be interviewed to cover the industry knowledge better. Furthermore, a selection criterion would be decided which would enable the selection of the right candidates for the sample. The right professionals should fulfill the criteria of seniority in position (Chief Executive or Senior Executive positions), expertise in mining industry (15 years of experience at least). The professionals will be contacted through the popular LinkedIn social network that enhances the interactions between professionals in the same sector of the economy. The interview data is qualitative as it determines the opinions of the mining experts on the potential core competencies that may improve the future performance of the mining companies (Sivakumar, Kannan, & Murugesan, 2015). The professionals would be interviewed with open-ended questions which would include the expert opinions. Furthermore, the professionals would also be given a survey that would use close-ended questions. The questions would be closed-ended; however, the respondents would be allowed to provide direct responses as well, if necessary. The Likert scale would be used for the answers of these close-ended questions.
Qualitative Analysis of Secondary Sources:
Apart from the interview, the qualitative research would use content analysis of secondary resources like YouTube Videos, Annual Reports of the company, other publications, and research reports. Content Analysis is important in the data collection process. It is effective in the analysis of the qualitative data that illustrate the adoption of the core competencies in the mining corporations. Through the YouTube platform, I must observe how various mining companies integrate technology in all the mining processes to enhance effectiveness and efficiency (Jia, Diabat, & Mathiyazhagan, 2015). For example, I will analyze the robotic systems that are effective in facilitating the innovation processes in the mining sector. The data of the qualitative analysis would be analyzed using the SPSS Software.
In-Depth Corporate Review Analysis:
Corporate reviews are necessary for the determination of the strategies that the mining organizations are using to adopt the core competencies in the business processes. Thus, I will review the annual reports on the websites of various companies to understand the measures that are being planned to enhance the future performance of the organization in the competitive mining sector (Kalabin, 2015). For instance, the company management may provide a budgetary allocation to finance the automation of the mineral exploration activities. The in-depth corporate review would provide data on the actual goals and strategies that the organizations are adopting to improve the capacities to benefit from the positive effects of the core competencies (Silvestre, 2014). The data mining process will ensure the collection of recent data and information from scholarly books and journals, on the topic of new trends and competencies in the mining sector.
The data are from the primary and secondary sources. The primary sources offer original data and information in the area of mining business models. The interview, observation, and questionnaire techniques provide primary data as they illustrate the actual thoughts and experiences of the respondents in the adoption of the core competencies in the mining sector (Gürtunca, 2018). The secondary sources of data and information illustrate the existing evidence on the topic of mining business models. The existing information is obtained from the websites of the companies in the contemporary mining sector, books on the topic of mining, and scholarly articles on the future of the mining industry.
Limitation of the Research:
The research is limited regarding covering the whole mining industry. The sample size of 20 professionals from such a big industry does not necessarily reflect upon the true opinions of the whole industry. Furthermore, this also restricts the implications of this research for the industry as it could be considered as limited because of a lack of access to primary data sources from the industry.
References
Amit, R., & Zott, C. (2001). Value creation in E‐business. Strategic Management Journal, 22(6-7), 493-520.
Becker, T. (2017). The impacts of Industry 4.0 – mining infrastructure & construction. Inside Mining, 10(4), 24-25.
Clifford, M. J., Perrons, R. K., Ali, S. H., & Grice, T. A. (2018). Extracting Innovations: Mining, Energy, and Technological Change in the Digital Age. CRC Press.
Gürtunca, R. G. (2018). Mining below 3000m and challenges for the South African gold mining industry. In H. P. Rossmanith, In Mechanics of Jointed and Faulted Rock (pp. 3-10). Routledge.
Hardy, L., Heller, S., Faltyn, R., & Stefanaki, A. (2017). The future of European mining: What should our mining industry learn from the Skouries and Rosia Montana community gold conflicts. In EGU General Assembly Conference Abstracts, 19, p. 19039. Vienna.
Ilankoon, I. M., Tang, Y., Ghorbani, Y., Northey, S., Yellishetty, M., Deng, X., & McBride, D. (2018). The current state and future directions of percolation leaching in the Chinese mining industry: Challenges and opportunities. Minerals Engineering, 125(2018), 206-222.
Jia, P., Diabat, A., & Mathiyazhagan, K. (2015). Analyzing the SSCM practices in the mining and mineral industry by ISM approach. Resources Policy, 46(2015), 76-85.
Kalabin, G. V. (2015). Integrated development of mineral mining and processing regions—real mechanism of stagewise transition to ecological–and-economic model of social modernization. Journal of Mining Science, 51(2), 415-422.
Lawrence, S., & Davies, P. (2015). Innovation, adaptation and technology as habitus: the origins of alluvial gold mining methods in Australia. Archaeology in Oceania, 50(1), 20-29.
Lodhia, S., & Hess, N. (2014). Sustainability accounting and reporting in the mining industry: Current literature and directions for future research. Journal of Cleaner Production, 84(2014), 43-50.
Makinde, O. A., Ramatsetse, B. I., & Mpofu, K. (2015). Review of vibrating screen development trends: Linking the past and the future in mining machinery industries. International Journal of Mineral Processing, 145(2015), 17-22.
Marr, B. (2018, March 14). How Blockchain Could End The Trade In Blood Diamonds – An Incredible Use Case Everyone Should Read. Retrieved December 18, 2018, from Forbes: https://www.forbes.com/sites/bernardmarr/2018/03/14/how-blockchain-could-end-the-trade-in-blood-diamonds-an-incredible-use-case-everyone-should-read/#384c57d8387d
Morrisa, M., Schindehutte, M., & Allen, J. (2005). The entrepreneur’s business model: toward a unified perspective. Journal of Business Research, 58(2005), 726-735.
National Research Council. (2015). Emerging workforce trends in the US energy and mining industries: a call to action. National Academies Press.
Pisani, B. (2012, August 28). The Billion Dollar Business of Diamonds, From Mining to Retail. Retrieved December 13, 2018, from CNBC: https://www.cnbc.com/id/48782968
S.K.Chaulya, & G.M.Prasad. (2016). Chapter 7 – Application of Cloud Computing Technology in Mining Industry. In S.K.Chaulya, & G.M.Prasad, Sensing and Monitoring Technologies for Mines and Hazardous Areas | Monitoring and Prediction Technologies (pp. 351-396). Elsevier Inc.
Silvestre, B. S. (2014). Are cleaner production innovations the solution for small mining operations in poor regions? The case of Padua in Brazil. Journal of Cleaner Production, 84(2014), 809-817.
Sivakumar, R., Kannan, D., & Murugesan, P. (2015). Green vendor evaluation and selection using AHP and Taguchi loss functions in production outsourcing in mining industry. Resources Policy, 46(2015), 64-75.
Trudel, B., Nadeau, S., Zaras, K., & Deschamps, I. (2015). Managing equipment innovations in mining: A review. Work, 51(4), 731-746.
Verma, S., & Chaudhari, S. (2016). Highlights from the literature on risk assessment techniques adopted in the mining industry: a review of past contributions, recent developments, and future scope. International Journal of Mining Science and Technology, 26(4), 691-702.
Zhironki, S. A., Tyulenev, M. A., Zhironkina, O. V., & Hellmer, M. C. (2016). The global determinants of mining higher education development. Metallurgical and mining industry, 2(2016), 62-67.
