Sustainable Development using Big data and Cloud Computing
Big data and cloud computing are likened and equated to the “Industrial Revolution” in terms of technological innovations, structural change, and the sources of economic growth.
The uses of these technologies by businesses, governments, non- government organizations, and consumers are rapidly increasing in the developing world.
This blog shows that the uses of Big Data and cloud technologies, often in combination with other technological applications, can support the implementation of the 2030 Agenda for Sustainable Development, and its seventeen different Sustainable Development Goals (SDGs).
Advancing on the capability of developing countries to take an active part in the Big Data and cloud ecosystems will, therefore, become increasingly important for accelerating progress in various targets, whether related to fighting hunger, mitigating climate change, improving health and education, or boosting productivity.
For example, an intriguing application of Big Data and the cloud has been in improving water supply availability and reliability. The deployment of Big Data and the cloud has greatly empowered customers and forced water providers to be more accountable, efficient, and transparent.
Tools and applications have been built to improve the performance of government agencies, water aid groups, and other actors as well as to provide information directly to end customers.
Various approaches have been used by a number of organizations involved in improving the water supply situation in the Global South. Some of them include the following.
In cities with irregular and intermittent water supplies, the startup company NextDrop utilizes data gathered from cellphone users to predict when water would be available.
Utility employees call NextDrop’s voice response system when they open water valves. The system sends a text message to local residents 30–60 minutes before water delivery.
Residents are contacted randomly by the system to verify the accuracy of the information that valve men provide. Updates from utility employees are used to generate Google Maps-based streaming visual data, which can be tracked by engineers to know valve status in real-time.
NextDrop charges the consumer Rs.10 (about US$0.16) per month. The service was started in 2011 and in the first five months, it had over 10,000 customers.
The NGO Water for People uses Google’s data-tracking technology to assess the real-time performances and functioning of its water supply projects.
Its cellphone-based app Field Level Operations Water (FLOW) helps to monitor the performance of water projects by providing a way to collect, manage, analyze, and display geographically referenced data. For instance, individuals on the ground can report information about broken water pumps.
Mobile devices are used to collect data and photos from water distribution points. They are then uploaded to a dashboard for real-time analysis. Data can be collected even in the absence of mobile connection.
In such cases, information is automatically transmitted when the devices are connected. The data collected this way are combined with visual map-based reporting tools. As of 2015, over 200 organizations including UNICEF and Millennium Water Alliance were reported to use FLOW.
Likewise, in the healthcare sector, take the case of mothers2mother (M2M), a South African NGO. It is combining the cloud with database technology and mobile services to fight the transmission of HIV/AIDS from mother to child.
Using the cloud, M2M digitizes patient records and shares them with counselors across the M2M networks, consisting of over 700 sites in Sub- Saharan Africa. The patient records contain information on treatment plans and advanced reporting tools, which would allow M2M to respond quickly.
The use of Big Data and cloud solutions provide an opportunity to leapfrog and overcome barriers related to information and communications technology (ICT) infrastructure and use.
The advantages of Big Data and cloud solutions can be enhanced further by combining them with other technologies and tools such as mobile phones and mapping applications to facilitate the flow of information in a diverse range of economic activities.
In this blog, we review factors that are driving the development of Big Data and cloud industries in the developing world, examine their potential impacts and look at the roles of businesses and policy makers in order to facilitate the adoption and effective utilization of these technologies.
We present a framework for evaluating the attractiveness of Big Data and the cloud with reference to the evolving needs, capabilities, and competitive positions of developing countries.
Definitions and Concepts
Before proceeding with the analysis, it may be useful to provide some clarifications on definitions and concepts that will be used throughout the blog.
This section explains what we mean by Big Data, the cloud, different kinds of cloud applications, the main stakeholders in the cloud ecosystem, and how the cloud and Big Data are related.
Cloud Computing and Cloud Services
Cloud computing has been defined by the US standardization body, the National Institute of Standards and Technology (NIST), as follows:
Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.
Cloud computing involves hosting applications on servers and delivering software and services via the Internet. In the cloud model, companies can access computing power and resources on the “cloud” and pay for services based on usage.
This contrasts cloud computing from the traditional, ownership-based model of IT assets and resources. One way of describing cloud services is that they are services that are provided and used by clients “on demand at any time, through an access network, using any connected devices [that use] cloud computing technologies.”
There are different categories of cloud services and applications. The three types most commonly referred to are Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).
Infrastructure as a Service (IaaS): In IaaS, compute power and storage space are offered on demand. IaaS can provide server, operating system, disk storage, and database, among other things. One of the main advantages of IaaS is that it offers rapid elasticity and flexibility.
Amazon is one of the biggest IaaS providers. Its Elastic Compute Cloud (EC2) allows subscribers to run cloud application programs. IBM, Vmware, and HP also offer IaaS. China’s Huawei provides IaaS solutions for operators, governments, and enterprises with data center IT infrastructure.
Platform as a Service (PaaS): Applications are developed and executed through platforms provided by cloud vendors. This model allows a quick and cost-effective development and deployment of applications.
PaaS is often used by application developers working on mobile applications. Some well- known PaaS vendors include Google (Google App Engine), Salesforce.com, and Microsoft (Windows Azure platform).
As another example, the US-based start-up, Cumulux, specialized on building, operating, and managing PaaS-based solutions, which was acquired by India’s Aditi Technologies.
Some facilities provided under the PaaS model include database management, security, workflow management, and application serving.
Software as a Service (SaaS): It is a software distribution model, in which applications are hosted by a vendor and made available to customers over a network.
The provider licenses an application to customers for use as a service on demand. With the SaaS, users do not need to hire professional IT staff to install and use the software.
SaaS is the most widespread form of cloud service. Some well-known examples include Google email, Google Apps, and Salesforce.com’s customer relationship management software. As a developing world-based example, MTN offers SaaS applications for micro-finance institutions.
SIGNIFICANCE OF MOBILE PHONES IN BIG DATA AND THE CLOUD
The use of mobile devices, rather than personal computers, to access Big Data- and cloud-based applications stand out as a particularly appealing and promising choice for developing economies, especially the least developed countries (LDCs).
Among the most compelling reasons is that less than a third of the population in developing countries owned a PC in 2015, compared with a cell-phone subscription penetration of 92 per 100 inhabitants.
In India, for instance, mobile phone subscriptions reached one billion in 2015, which is 83 percent of the country’s population. On the other hand, India’s PC penetration in the same year was estimated at 10 percent.
Indeed, more people worldwide have a mobile subscription than have access to a clean toilet, electricity, or clean drinking water.
Unsurprisingly, there are already many successful examples of projects involving Big Data- and cloud-based mobile computing solutions in developing economies. This blog focuses on more general issues of Big Data, the cloud, and mobile phone combination to deliver value to end-users.
In order to illustrate the above point, consider the use of mobile computing solutions to deal with the shortage of clean drinking water.
It is estimated that women and girls in developing countries spend between three minutes to three hours per day in collecting water for drinking, cooking, cleaning, laundering, etc.
Reducing this time would give them more time to spend on productive economic and social endeavors such as agriculture and farming-related activities, focusing on maternal and child- health-related issues and attending school.
Various approaches have been reported involving the cloud and mobiles in combination with mapping applications and other technologies to facilitate information flow and to improve water supply availability and reliability.
An innovative use of Big Data- and cloud-based mobile computing solutions has been in minimizing water loss due to leaky pipes. One estimate suggested that 60 percent of water worldwide is lost due to leaky pipes.
It should, therefore, come as no surprise that improving water management is a key target under the Sustainable Development Goals.
Target 6.4 says: “By 2030, substantially increase water-use efficiency across all sectors and ensure sustainable withdrawals and supply of freshwater to address water scarcity and substantially reduce the number of people suffering from water scarcity.”
Other applications involving Big Data- and cloud-based mobile computing solutions have helped to deal with developmental, political, and social issues such as improving health outcomes, fighting corruption, and reducing poverty.
For instance, such solutions have transformed health care by driving down costs, changing workflow, improving business continuity, and making an adequate provision for disaster recovery.
Big Data- and cloud-based mobile computing solutions have boosted the productivity of traditional sectors such as agriculture and farming as well as that of enterprises in the modern sector.
For instance, the mobile application, iCow, which helps small-scale Kenyan dairy farmers track and manage cows’ fertility cycles, has helped to increase milk production by 2–3 liters per cow per day.
No less important is the role of the data and information generated through Big Data- and cloud-based mobile computing solutions in the creation and functioning of the market.
The data and information play an especially important role in developing countries because factors such as underdeveloped intermediary institutions and informational opaqueness of small and young firms have acted as a barrier to the functioning of markets in these countries.
For instance, as of September 2013, the information created by the cloud- mobile platform, Agri-Life, which provides financial institutions and suppliers “near-real-time information” on farmers’ ability to pay for services, facilitated over US$2 million in revolving credit lines to about 120,000 small farmers in Kenya and Uganda.
The Deployment of Big Data- and Cloud-Based Mobile Computing Solutions
The cloud reduces infrastructure costs, which can be illustrated with the deployment of PaaS. For instance, the South African start-up, Nomanini sells a “business in a box,” a cloud-based mobile prepaid airtime machine, to small informal entrepreneurs, which allows them to set up a “mini-business.”
It is called Lula (meaning “easy” in the Zulu language), which is especially useful for providing services to support individuals engaged in small business and informal economic activities such as taxi drivers and “on the go” vendors. Lula generates and prints codes which people purchase to add minutes to their mobile phones.
Lula runs on Google App Engine, which is the same infrastructure that powers Google’s own applications such as Google Calendar, Gmail, and Google Docs.
That is, Google provides the framework and storage and manages servers for Lula. Google also provides services to software applications associated with Lula beyond those that are available from the operating system (known as middle-ware).
In addition, Google provides runtime- related services such as supporting the execution of programs required to print vouchers using Lula.
Nomanini’s goal is to reach one million informal market merchants by 2020. That also allows the company to build up a huge amount of data about the informal markets.
An IaaS model allows delegating functions such as storage and computing to the cloud provider. For instance, according to biNu’s developers, by moving much of the processing to the cloud, biNu works ten times faster than regular mobile web browsers. In this way, biNu creates a virtual “smartphone in the cloud” for a user.
It makes graphics and text on the cloud and the data is sent back to the phone as tiny images.
An advantage of sending the data as images is that the text can be displayed in any language irrespective of the language a phone is programmed to handle. Each image consists of only one or two packets of data of less than one kilobyte (KB) each.
Information is not sent twice. The servers remember the information that is sent before and provides only new instructions that are needed to change the content on the screen. The cloud also provides the flexibility of scaling up uses when the demand increases.
Appropriateness, Effectiveness, Feasibility, and Worthwhileness of Big Data and Cloud-Based Mobile Computing Solutions in the Developing World The high penetration of mobile phones in developing countries makes Big Data- and cloud-based mobile computing solutions among the most appropriate and useful technologies.
The least gap between developed and developing countries is observed for mobile subscriptions compared to most ICTs, which makes Big Data-and cloud-based mobile computing solutions particularly promising.
The cloud has increased the effectiveness and enriched the uses of cell phones. New technological developments, related to cellphones and the cloud, are contributing to a more rapid diffusion of Big Data- and cloud-based mobile computing solutions.
First, less sophisticated cell phones are now “cloud- ready” as a result of recent developments. A cell phone capable of running a browser can access a number of mobile cloud applications. Low-cost phone users can thus tap into applications that are currently accessible only through smartphones.
Second, consumers in developing countries are using increasingly sophisticated devices facilitating the diffusion of Big Data- and cloud-based mobile computing solutions. According to the NPD Group, in the third quarter of 2013, China’s smartphone penetration rate was 55 percent.
In the fourth quarter of 2013, smart-phone sales in India grew by 167 percent. Handset makers, meanwhile, are offering ultra-cheap smartphones. To take an example, China’s mobile chip supplier, Spreadtrum Communications and Mozilla, announced that they have teamed up to launch a US$25 smartphone for the world’s emerging markets.
The unavailability and high costs of bandwidth can be the major challenges in offering bandwidth-intensive applications in developing countries. In countries such as South Africa, whereas bandwidth is available, the price of broadband is a critical barrier for using cloud-based services.
Thus most mobile phones used in developing countries are only adequate for non-bandwidth intensive applications such as text messaging.
In order to demonstrate the usefulness, appropriateness, and effectiveness of Big Data- and cloud-based mobile computing solutions in developing countries, we discuss an application to enhance transparency and fight corruption in Guatemala.
In 2010, a national survey of the beneficiaries of Mi Familia Progresa (Mifapro) was administered with low- cost mobile phones and EpiSurveyor (free software) for data collection. Mifapro was the then President Alvaro Colom’s flagship social program.
It was a conditional cash transfer (CCT) aimed at improving the quality of life of poor families. Before 2010, similar surveys were carried out using paper-based data collection methods, which suffered from drawbacks such as frequent errors, storage burdens, and the high costs of double data entry.
While handheld devices not connected to the cloud, such as personal digital assistants (PDAs) are sometimes used to replace paper-based methods, they have their own shortcomings.
The data need to be downloaded to laptops in frequent intervals are not available in real-time, and may be corrupted or even lost if PDAs are damaged, misplaced, or stolen.
In this way, mobile-based clouds perform well from the standpoint of disaster recovery. Big Data- and cloud-based mobile computing solutions helped to overcome these limitations.
The 2010 CCT survey relied on EpiSurveyor installed on entry-level mobile phones to collect information from 500 Mifapro beneficiaries, mainly indigenous women. It was funded by the United Nations Foundation, the Vodafone Foundation, and a World Bank Development Marketplace Grant.
It drastically reduced the cost and enhanced survey accuracy. The results accelerated the implementation of a nationally representative beneficiary survey of the CCT program.
EpiSurveyor was arguably the first cloud application for data collection in international development. The process and results were compared with the 2009 paper-based survey conducted with 200 beneficiaries.
It was reported that Big Data- and cloud-based mobile computing solutions reduced average interview cost by 71 percent and average interview length by 3.6 percent.
The data quality was reported to improve and 89 percent of the interviewers preferred Big Data- and cloud-based mobile computing solutions methods compared to the paper-based survey. In contrast to paper- or PDA-based approaches, the use of Big Data- and cloud-based mobile computing solutions resulted in no data loss.
Other worthwhile applications of Big Data- and cloud-based mobile computing solutions concern financial services such as stock trading.
In October 2010, Intel announced an agreement with an alliance of seventy companies, including the Bombay Stock Exchange (BSE) and CtrlS to develop hardware and software for an open and interoperable cloud.
The Open Data Centre Alliance (ODCA) works to address security, energy efficiency, and interoperability.
The BSE expects that the new trading platforms supported by Big Data- and cloud-based mobile computing solutions will broaden the participation of younger Indians, deepen and widen asset classes traded in pension funds, insurance, and mutual funds and others.
As noted above, as of 2015, only 10 percent of Indians owned a computer, but more than a billion had mobile subscriptions.
Key Areas of Deployment and Impacts
Impact on the Healthcare System
Some of the most dramatic impacts of Big Data- and cloud-based mobile computing solutions in developing economies have been documented in health care.
For instance, the South African NGO mothers-2-mothers (M2M) system/approach combines the cloud and mobile technologies with a database to fight HIV/AIDS transmission from mothers to children.
Note that annually over 400,000 babies are born with HIV infected in Africa. This is partly due to the lack of knowledge about the disease and treatment options as well as the stigma associated with HIV.
M2M digitizes patient records and shares with doctors, nurses, mentor mothers, and counselors across its networks of over 700 sites.
The records contain information on treatment plans, and advanced reporting tools, which allow a quick response. Women in villages authenticate children’s medication with text messages.32 As of 2011, M2M has served more than 1.5 million women in nine SSA countries. It is estimated that the cost is less than US$75 per beneficiary.
As a further example, in Malawi, the cloud-based Mother Infant Pair (MIP) mobile application was developed by D-Tree International and designed for Health Surveillance Assistants (HSAs) working with pregnant HIV-infected women.
The MIP was developed according to the Community-Based Maternal and Neonatal Care (CBMNC) guidelines, which aims to regulate community infant care until the child is two years old. All HSAs are properly trained on CBMNC guidelines as well as on MIP.
During the home visits before and after the birth, the MIP-installed mobile phone takes the HSA over the questions that need to be asked to the client, as well as the associated advice that needs to be communicated. MIP uses the General Packet Radio Service (GPRS).
Data transmission using the GPRS costs US$0.00003/KB, which is significantly lower than the cost of an SMS, which is US$0.03/KB. The data is sent to a cloud server and can be downloaded from the Internet. The average size of submitted forms is 3–5 KB.
Moving to a different topic, the reduction of maternal and infant mortality is a key priority in many countries. For example, the SDG target is to reduce the global maternal mortality ratio to less than 70 per 100,000 live births by 2030.
As of 2010, about 2,500 midwives were working in 652 primary health care centers serving 10.7 million people in Nigeria.37 Big Data- and cloud-based mobile computing solutions are well positioned for contributing towards this goal.
In order to collect data from midwives, Nigeria’s Mobile Application Data Exchange (MADEX) has developed an SMS- based data collection platform.
Data sent by midwives is forwarded to the central cloud-based server. Due to the simplicity of the processes, cloud-based systems such as MADEX are appropriate for technologically less savvy users.
The data can also be tagged with a GPS coordinate, pictures, video, and audio. If there are signals of an outbreak of malaria, Ministry of Health officials and other health workers in the area receive a real-time notification via text message.
An innovative application in the early phases of development can help to identify counterfeit or sub-standard drugs. Individuals find it difficult to make decisions in the face of inadequate information as to whether a drug they are buying in order to save a life is genuine or not.
While buying a drug at a pharmacy store, a customer can find a twelve-digit code by scratching a sticker on the surface of the package and then send a text message to a given number.
The code sent by the customer is matched with the one registered by the pharmaceutical company in HP’s cloud database. The customer then receives a response back that tells whether the drug is counterfeit or genuine.
Although this application provides obvious commercial benefits to drug manufacturers and patients, one of the most important ones is that it helps save lives by enabling customers to check the authenticity of life-saving drugs.
Impacts on Business Processes, Productivity, and the Creation of Markets
In this section, we discuss the impacts of Big Data- and cloud-based mobile computing solutions on business processes and productivity and the creation of markets.
Big Data- and cloud-based mobile computing solutions allow for better workflow by saving time and allowing data to flow automatically into the clouds.
Let us now consider such possibilities in small- and medium-sized enterprises (SMEs). The South Africa- based telecommunications company MTN launched pilot cloud computing services targeting SMEs in Uganda, Cameroon, Côte d’Ivoire, Ghana, Nigeria, and South Africa.
Following the pilot projects, it launched a suite of cloud services for SMEs in Ghana and Nigeria in December 2012.
For instance, MTN MyOffice, a suite of SME-focused ICT solutions designed to enhance the way businesses work and collaborate is available in Nigeria. The subscribers of MTN’s SME Closed User Group (CUG) can pay a flat monthly fee and enjoy zero- and call services among their staff.
The service is available to SMEs with 2–199 employees. According to MTN, this offering has already been adopted by SMEs in manufacturing, hospitality, microfinance, and advertising.
The MTN Cloud offers packages to manage the infrastructure and platforms to support business functions such as accounting, human resource, customer relations management, email, and video conferencing, storage and back- up for small businesses.
The business software and data are stored on a cloud which ends- users can access through mobile phones as well as a PC.
The roles of Big Data- and cloud-based mobile computing solutions in market creation are much less appreciated but may be quite important. Kenya’s Musoni Systems established the world’s 100 percent mobile microfinance institution in 2009. Its cloud-based core banking solution has a huge amount of information on small-scale financial service providers as well as low-income consumers.
Among the key functions of markets are to match buyers and sellers, facilitate the exchange of information, goods, services, and payments and to provide an institutional infrastructure, such as a legal and regulatory framework.
Factors such as transportation and communication infrastructures and intermediary institutions are essential for the creation and functioning of markets.
Regarding buyer/seller matching services, more broadly, we discuss how Big Data- and cloud-based mobile computing solutions have facilitated the dialogue, interaction, and coordination between producers and users of goods and services in developing countries.
Market creation can occur through various mechanisms and with varying effects on the market participants.
The HP’s cloud database was designed to provide information as to whether or not a drug is genuine. Lula owners act as intermediaries, matching buyers with sellers of airtime.
Developing world-based farmers are often paid low prices for their products. On the other hand, the poorly informed farmers pay higher prices in order to obtain the needed inputs that market conditions dictate.
Big Data- and cloud-based mobile computing solutions have made it possible to fight these problems.
In Mauritius and Ghana, Esoko, a mobile-enabled cloud service, collects and provides information to farmers on such topics as current market prices, bids and offers, weather, and tips.
Advisories are also sent by voice messages and a live call center of agricultural experts is made available.
SMEs are especially likely to benefit from the data and information created by Big Data- and cloud-based mobile computing solutions because developing economies are characterized by the lack, or poor performance, of credit rating agencies providing information about the creditworthiness of SMEs.
A national credit bureau would collect and distribute reliable credit information and hence increase transparency and minimize the banks’ lending risks. Many emerging economies lack such an agency and some have a poorly functioning one.
This situation puts SMEs in a disadvantaged position in the credit market. SMEs tend to be more informationally opaque than large corporations because they often lack certified audited financial statements and thus it is difficult for banks to assess or monitor their financial conditions.
Discussion and Concluding Comments
Developing economies’ broad political, economic, and social contexts have given rise to the growth of Big Data- and cloud-based mobile computing solutions.
Unsurprisingly, a number of creative approaches to the deployment, operation, and use of Big Data- and cloud-based mobile computing solutions have already been reported in the developing world.
While initial investment costs may be relatively high in some cases, possible savings due to efficiency gains, improved quality, and other advantages are obtained, which often exceed the initial investment. The simple fact that the data are created digitally as opposed to being digitized manually dramatically reduces the costs.
The cost savings that could be achieved through the immediate digitization and data transmission and automated data aggregation were much greater than the purchasing and data transmission costs of mobile phones.
One advantage of the cloud is that if a device fails or is lost, the information is still securely saved in the cloud. There is no need to worry about data loss in issues such as theft and burglary involving cellphones and computer crash, which are not uncommon.
We noted earlier that health organizations in the USA suffer from the lack of skills related to high- level project management. The shortage of skills and talent is a more serious problem in developing countries.
Since clients can access resources from a web browser, they are not required to install or download anything on their devices. The cloud is thus a more appropriate choice.
The low penetration rates of computers, the Internet, and smartphones, and the fact that a large proportion of the population lacks a documented home address make this an attractive option economically and technologically.
Mobile prepaid services do not require Internet access or a bank account and can be purchased in small or large amounts.
A further reason for the popularity of such vouchers is that it is difficult to distribute physical vouchers because of theft and fraud risks.
The lack of availability and quality of cloud-related infrastructure have hindered cloud adoption in developing countries. In SSA, only 53 percent of the urban population and 8 percent of the rural population have electricity.
Developing countries perform relatively poorly compared to developed countries in most factors related to cloud computing. On the other hand, some constraints that have hindered the diffusion of the cloud in developed countries are less restrictive in developing ones.
For instance, due to the requirement of stringent security measures in order to comply with the HIPAA requirements, healthcare organizations in the USA are reluctant to use the cloud despite significant potential efficiency gain.
Barriers to E-Commerce in Developing Economies
As noted earlier, prior research has identified e-commerce barriers in terms of three forms of negative feedback systems: economic, socio-political, and cognitive.
GS-based firms face a number of economic barriers, such as the high costs of ICT infrastructure, equipment, and operation and the lack of purchasing power. Prior research suggests that firms which use technologies that are more web-compatible and with a higher number and variety of web functionalities (e.g., presentation of contents;
the capture of transactions securely, and personalization, etc.) are more likely to adopt e-commerce. A larger proportion of firms in developing economies than in more industrialized countries lack such technologies.
The unavailability of credit cards is another major hurdle. This has been a major barrier since as of 2013, only 3 percent of the Sub-Saharan African population had credit cards.
In Africa, the lack of viable payment systems is considered to be a bigger hurdle than the lack of connectivity. There are also problems associated with the lack of economies of scale in small developing countries.
Slow Internet diffusion in developing countries can be attributed to market and infrastructural factors controlling the availability of ICTs. A large proportion of the population in many developing economies also lacks the basic prerequisites to Internet use.
Due to the above barriers e-commerce provides, in developing economies they are exploring alternative business models.
A large proportion of e-commerce in Asian economies such as China, Indonesia, and India takes place on a cash on delivery (CoD) basis. The CoD system, however, has some major drawbacks, especially from the businesses’ perspective.
In Indonesia, for instance, it is a common practice for customers to cancel their purchases after the products are delivered.
In other cases, customers order more than one unit of the same product (e.g., in different sizes, and colors), then choose the one they like after the products are delivered.
Socio-political barriers can be explained in terms of formal and informal institutions. They often tend to be more difficult and time- consuming to overcome than technological barriers.
The literature provides abundant evidence that legal barriers are among major hindrances to e-commerce in the developing world.
A survey conducted among Brazilian consumers indicated that the low e-commerce adoption rate was related to government regulations such as concern about privacy and security, lack of business laws for e-commerce, inadequate legal protection for Internet purchases, and concern over Internet taxation.
Likewise, in China, the lack of institutional trust due to the weak rule of laws was a major barrier to e-commerce.
Cognitive factors are related to mental maps of individuals and organizational decision makers. Some analysts argue that cognitive barriers are more serious than other categories of barriers in developing countries. Many effects such as inadequate awareness, knowledge, skills, and confidence serve as cognitive feed-backs.
In developing countries, organizations’ human, business, and technological resources, a lack of awareness and understanding of potential opportunities, risk aversion, and inertia often lead to a negative cognitive assessment of e-commerce. Businesses are also concerned about handling demands during peak-load periods.
A final consideration with cognitive barriers is related to general and computer illiteracy and a lack of English language skills.
The Roles of Big Data and the Cloud in Overcoming Economic Barriers
The main attractiveness of the cloud is that it leads to a reduction in upfront investments and addresses constraints related to organizations’ human, business, and technological resources.
For instance, India’s Apeejay Stya and Svran Group, which is a US$1 billion-plus conglomerate, moved the entire IT functions including the mission-critical ones to AWS. The company reported that by doing so, it reduced IT staff from twenty-three to three and cut costs by over 80 percent.
A large number of firms and individuals in developing economies tend to use technologies that lack web compatibilities and have a limited number and variety of web functionalities. For instance, it is not possible to use low- end mobile phones to perform most e-commerce activities.
In this regard, note that in 2011, India had more than 700 million mobile phone users, which was about forty times the number of Internet users in the country.
Over 50 percent of these phones had only voice and text messaging capabilities. Technology companies have come up with innovative solutions in order to overcome obstacles associated with accessing the cloud-based applications with technologies with limited functionalities such as low-end mobile phones.
To take one example, to cater to the needs of low- end mobile phone users, Hewlett- Packard has developed cloud-based SiteOnMobile to deliver Internet experience over low-end phones.
Many SMEs in India that have invested in e-commerce websites but they have not been able to benefit from them. SiteOnMobile enables them to define specific tasks on their websites.
One example of a task could be “Buy Solar Stoves.” SiteOnMobile makes those tasks accessible to their customers from mobile phones. For this purpose, HP introduced the concept of “Tasklets,” which are special types of “task-based widgets” that can be created by a user by “showing the action once on the browser.”
For the first time, the user performs the tasks on multiple websites using HP’s special browser. SiteOnMobile then automatically generates a widget- like interaction for that task for the user.
Let us assume that a user has created a tasklet of “book a Taxi.” In order to blog a taxi, the user does not have to go through several web pages to reach the blogging page.
SiteOnMobile will perform all the steps for the user for subsequent uses once the interactions are created in HP’s special browser.
The task-lets can be accessed by users via SMS or voice services. SiteOnMobile performs all the needed tasks on the cloud and sends back the result to the user over SMS.
For example, if an SMS “book a Taxi” is sent to a predefined SMS access code, a taxi will be booked and the user will receive back details about the taxi that has been booked.
Regarding the barriers associated with a low penetration of mainstream online payment methods such as credit cards, it was reported that foreign CSPs require cloud users to pay with credit cards. Among the encouraging developments is the emergence of local CSPs, which sell to non- credit card users.
In Africa, for instance, CSPs accept payments by the mobile payment system, MPesa. Likewise, given the unavailability of mainstream payment methods such as credit cards and the risks of existing mechanisms such as CoD, cloud-based payment mechanisms such as Alipay possess a high degree of attractiveness and utility.
Alipay Wallet’s features include payments at brick-and-mortar stores, transportation, and appointment at hospitals.
Merchants can also offer discounts, coupons, and special membership privileges to Alipay Wallet users. Users of Alipay can also make e- payments at brick-and-mortar shops.
In June 2014, the Chinese online grocery store Yihaodian, which is majority-owned by WalMart, launched a storefront on Alipay Wallet. It allowed customers to buy groceries from their Alipay Wallet app.
The Roles of Big Data and the Cloud in Overcoming Socio-Political Barriers
The cloud’s transformative potential has resulted in significant national political decisions to utilize this technology for key economic activities.
To some extent, such decisions addressed issues such as the lack of appropriate government regulations related to privacy and security, and the lack of institutional trust.
For instance, Brazil’s federal representative Ruy Carneiro presented a bill for the creation of a cloud computing framework and the introduction of data protection laws. The bill is intended to address the lack of regulations around data privacy protection.
It also addresses interoperability and standards for services provided. Likewise, India’s industry body, National Association of Software and Services Companies, has issued best practice security standards, procedures, and guidelines for its member companies. However, compliance is voluntary.
The Roles of Big Data and the Cloud in Overcoming Cognitive Barriers
Unlike client-based computing, cloud-based software is easier to install, maintain, and update. For instance, in the above examples, Demandware makes new features available to Clarins on a rolling basis.
Thus in order to expand e-commerce activities, Clarins is not required to undergo any major upgrade project or add staff for maintenance.
The cloud’s key features such as the ability to reduce upfront investments and handle business processes and transaction without the intervention of an organization have greatly increased the confidence of firms in developing economies.
According to a survey conducted by Vmware and Forrester in 2012, 80 percent of respondents in India believed that the cloud would help reduce IT costs, and 82 percent believed that it will help optimize IT management and automation capabilities.
Measures taken by global CSPs have also helped overcome cognitive barriers associated with e-commerce adoption.
Global CSPs such as Amazon and Google hold seminars for start-ups in India, Indonesia, and many other developing economies. There are also consultants, who teach businesses how to use the clouds of Amazon and other CSPs.
In addition, Google has teamed up with Endurance International Group to help African and Southeast Asian SMEs to launch online businesses.
Endurance helps SMEs set up Google My Business, which is a free service and helps customers find a business online. SMEs can pay for add-ons such as the creation of a full-blown website and launch of e-commerce.
In this way, firms’ e-commerce adoption constitutes a gradual process instead of a quick change.
Barriers That Still Remain and New Barriers That Have Emerged in the Big Data and Cloud Environment
Obviously, it is not possible for Big Data and the cloud to overcome all the barriers facing developing economies. These economies still face severe market and infrastructure constraints.
Most cloud services, for instance, rely on bandwidth, which is the most glaring shortcoming of most developing countries, especially in rural areas. Likewise, the cloud is not of much use to firms who lack access to basic needs such as electricity.
Cloud-based e-commerce solutions in these economies are provided using cloud servers located at distant data centers in foreign countries. For instance, India’s nationwide cab-booking service Getmecab uses Amazon servers. The closest servers are in Singapore.
Likewise, India’s Tata Communications opened a data center in Singapore to offer cloud services to foreign clients due to Singapore’s cutting-edge IT infrastructure, the availability of IT experts, and government incentives.
Due primarily to poor bandwidth in India, Tata Communications decided to locate the facility in Singapore, despite Singapore’s expensive land and high temperatures, which increase the costs of keeping the servers cool.
As of 2014, India’s national 3G coverage in India was 9 percent. In those cities where 3G coverage is available, the services perform poorly due to congestion.
Many governments have viewed the cloud as a disruptive technology with the potential to change the national competitive performance. They are also preoccupied with national security concerns regarding the sensitive data and information stored in the cloud.
Consequently, many governments in developing economies have pursued a somewhat protectionist agenda regarding the development of the cloud industry and market.
These barriers are especially problematic for global efficiency because technologies such as cloud are cross-border in nature.
The Indian government proposed a measure which requires companies operating in the country to locate part of their IT infrastructure in the country. This requirement was for providing law enforcement agencies ready access to encrypted data on servers in India.
This measure also prohibits businesses to move data related to Indian citizens and government organizations out of the country.
Failure to comply will be a criminal offense and responsible people will face prosecution. The guidelines of the central bank, the Reserve Bank of India (RBI), prohibit storing customer data outside India, which limits cloud adoption by financial services companies.
Similarly, due to concerns related to national security, currency control, and industrial policy, China has local data server requirements. The Chinese government has also expressed a desire to see the cloud industry dominated by local companies.
In addition, it wants Chinese companies to control a higher share of world cloud markets. To fulfill this desire, it has taken a number of measures. According to the NDRC, the government has viewed cloud computing as a strategic industry.
It is worth noting that companies in other strategic sectors are eligible for market protection. China has classified cloud computing as a value-added telecom service (VATS).
Under the Chinese regulatory regime, and in accordance with China’s WTO commitments, foreign- company ownership is capped at 50 percent in VATS ventures and 49 percent for basic telecom services. This means that foreign CSPs are required to find local partners in order to operate in China.
While the central government defines cloud computing as a value-added service, there is no specific “cloud computing” category in the license list of value-added services.
To deploy its Microsoft Office 365 in China, it is hosted by a Chinese domestic company by license requirement. Other foreign cloud providers such as Amazon, IBM, and SAP have followed similar models.
In the same vein, in September 2013, the then Brazilian President Rousseff asked the Congress to introduce regulations to require foreign companies to store data generated by Brazilians on local servers.
Among foreign ICT companies, there is widespread and growing disenchantment with the adequacy of the Brazilian regulatory system for the cloud industry. In the 2012 ranking of the Business Software Alliance of twenty-four countries, in terms of the cloud environment, Brazil finished last.
In the 2013 BSA Global Cloud Computing Scorecard, Brazil improved slightly and ranked twenty-second of the twenty-four economies considered.
The scorecard considered Data Privacy, Security, Cybercrime, Intellectual Property Rights, Support for Industry-Led Standards, and International Harmonization of Rules Promoting Free Trade and ICT Readiness, Broadband Deployment.
Brazil was among the countries showing the most improvement in their infrastructure score for 2013. Brazil also lacks an appropriate framework for the development of ICT standards and gives domestic service providers preferential treatment in public procurement.
Regarding the cognitive institutions, the cloud involves outsourcing IT functions. Some organizations hold the view that the adoption of the cloud model would result in the loss of control.
For instance, China’s state-owned enterprises (SOEs) exhibit a higher level of concern regarding data security: they have a tendency to distrust CSPs and are reluctant to outsource IT needs and move to the cloud.
Indeed, until not long ago, SOEs were not allowed to use outsourced data center services. There also have been concerns related to data security, which has made businesses cautious in spending on cloud services. A further limitation of cloud-based e-commerce solutions concerns the reduction in control over customer experience.
Discussion and Concluding Comments
While some of the barriers to e-commerce highlighted above could be mitigated through the use of clouds (e.g., the lack of human, business, and technological resources, the low level of computer illiteracy, etc.), other barriers (e.g., the lack of credit card, the lack of awareness and understanding of potential e-commerce opportunities), require broader efforts to overcome.
Some socio-political measures (e.g., by the Brazilian government and India’s NASSCOM) taken to facilitate the development of the cloud industry and market are likely to have positive effects on e-commerce.
Nonetheless, other sets of measures taken by national governments to protect economic and national security concerns, which are associated with the cloud’s radical and disruptive nature, are likely to have adverse effects on the healthy competition and may limit the choices available to businesses.
Buyers and sellers are thus likely to face different types of socio-political barriers to engage in e-commerce activities.
Reduction in control over customer experience and concerns regarding security in the cloud should also be taken into account to assess the potential of cloud-based e-commerce solutions.
Overall, the cloud has increased the confidence and capability and improved the competitiveness of firms in developing economies, especially of SMEs, to engage in e-commerce activities.
Cloud-based e-commerce infrastructures and applications, as well as retail solutions such as POS systems, are less expensive, which is especially important for SMEs. Another key benefit is that thanks to the cloud, businesses are less concerned about fulfilling demands during the peak data flow periods.
The experiences of economies such as China and India indicate that cloud-based e-commerce solutions provided by local and global CSPs have enriched the e-commerce ecosystems of these economies.
These CSPs’ cloud offerings have increased the breadth and depth of e-commerce offerings and have made it convenient and attractive for both buyers and sellers to engage in e-commerce activities.
In a further attempt to improve the ease with which firms can adopt cloud-based e-commerce, offerings by local and foreign companies are being bundled as solutions.
Case Studies of Diffusion and Impact of Big Data and Cloud Computing
Big Data and the cloud have become increasingly pervasive in SSA economies. According to the undersea cable operator, MainOne, the African cloud market was US$35.6 billion in 2015.1 The market research company, IDC estimated that South African cloud services market reached US$230 million in 2014.
According to IBM, as of 2014, about half of the medium and large businesses in South Africa and Kenya had adopted the cloud.
A survey of World Wide Worx and Cisco revealed that 44 percent of Nigerian businesses had plans to adopt the cloud in 2014. Another study found that at least 40 percent of businesses in Nigeria and Kenya were in the planning stages of Big Data projects in 2015.
Some economic sectors are more advanced than others in the adoption of Big Data analytics and the cloud. For instance, SSA- based firms in retail, telecoms, oil, and gas, and banking are most likely to use the cloud to handle large volumes of data transactions.
To take an example, in Nigeria and Angola, the oil industry has driven the investment in data centers. This industry exhibits a high degree of orientation towards the global market.
Most SSA economies in the past needed to rely on satellite for Internet connection. Satellite-based connections are expensive.
Moreover signals often need to take a 76,000 km round-trip to and from orbits. The resulting delays are especially disruptive and troubling for data-intensive applications or banking transactions.
In this regard, an important factor is that undersea cables have landed in some of these economies. Due to this, data centers are growing rapidly in Kenya and other countries.
Competitively priced fast and ultra-fast internet access is becoming widely available in SSA economies. The region’s telecom companies are using this as a selling point to attract customers.
For instance, Liquid’s ads in Zambia and Zimbabwe say that it takes a shorter time to download a movie than to prepare popcorn by microwave.
Major challenges and barriers to the Big Data and the cloud pathways include the lack of local infrastructures, unaffordability, and relatively narrow local offerings. For instance, according to Seacom, in 2014, 90 percent of African internet content was hosted outside the continent.
The resulting latency has a visible effect on video streaming and other bandwidth consuming applications. Such services and applications also cost more on the continent.
The Current State of Big Data and Cloud Market
A number of creative Big Data- and cloud-based apps have been developed that are unique to SSA economies.
The Higher Education Alliance for Leadership through Health, a consortium of seven universities (in Kenya, Ethiopia, the Democratic Republic of Congo, Tanzania, and Uganda), works with industry experts to extend education through virtual labs that students access remotely.
South Africa’s Center for Higher Education Transformation lets African universities access and manipulate its performance data stored on a Google platform. Also, Google has provided its cloud-based Apps for Education to universities in Rwanda, Kenya, and Mauritius.
In 2009, Microsoft donated 250,000 laptops to teachers in Ethiopia. The software in the laptop is managed by the US company FullArmor through Microsoft’s Azure cloud platform. Teachers can download curriculum; maintain, view, and track academic records; and transfer student data securely.
Farming and Agriculture
Improving agricultural productivity is likely to be among the most positive effects of Big Data in SSA economies. It is estimated that the average African small-holder farmer produces only a quarter to half of the productive potential.
Big Data can help them make full use of their productive potential. Big Data can also help farmers reduce costs by providing access to detailed information about irrigation and reduce wastage in resources.
A number of efforts and initiatives are being undertaken to digitize SSA’s agricultural activities. A promising area of Big Data and cloud utilization to increase agriculture productivity is soil infrared spectroscopy.
Data about soil characteristics such as texture, organic matter, and fertility help determine fertilizer needs and can be used as a basis for precise prescriptions.
One way to get information about soil characteristics is to use orbiting satellites, which can collect data in a cost-effective manner by measuring electromagnetic radiation reflected from farmlands.16 Efforts have been made to develop national and regional databases for soil properties.
Green Dreams’ iCow helps farmers track and manage cows’ fertility cycles. It informs them about important days of cow gestation periods, collects and stores milk and breeding records, and finds the nearest veterinarian and other service providers. A simple system involving Google Docs is also used.
If Green Dreams and the vet can’t answer a question, the question is uploaded to the iCow system and vets send messages among themselves to come up with the best answer, which is then forwarded to the farmer. As of 2012, 42,000 farmers were using iCow, which increased milk production by 2–3 liters per cow per day.
A National Geographic article reported the story of a Farmer Thuo, who experienced a substantial increase in his yields and improvement of his animals’ health thanks to the adoption of iCow.
By applying the knowledge (e.g., fodder production, hygiene, and animal diseases) that he received from iCow, he was able to double the production of milk from his cows.
The iCow system also helped him manage challenges such as food shortages that he had faced in the past. Before he started using iCow, Thuo lacked the knowledge and skills required to measure the cost per liter of milk.
He started keeping records of his farming activities. Thanks to the confidence that iCow gave him as a farmer and a businessman, he was considering to expand into pig farming.
Business Process and IT Outsourcing
South Africa’s call center agents and software developers are increasingly leaving dedicated facilities and embracing cloud-based systems, boosting productivity by 20 percent. Because they don’t need to own and maintain equipment and can log in from anywhere using IP lines, they have lowered their capital investments.
Banking and Finance
In South Africa, Nedbank has automated business processes through the cloud, and MTN offers SaaS applications for micro-finance institutions. Also, in 2011, Kenya’s Safaricom launched Safaricom Cloud and started hosting the Mpesa mobile money service locally.
Furthermore, in early 2013, the Commercial Bank of Africa signed a cloud infrastructure deal with HP to increase its storage capacity by 50 terabytes.
Environmental Monitoring and Protection
An article published in the Huffington Post explains that drones are used to track and prevent elephant poaching in Burkina Faso and to prevent rhino poaching in Southern Africa. In 2013, scientists completed an unmanned aerial survey of wildlife in Burkina Faso’s Nazinga Game Ranch using drones.
Since drones are cheaper and can be launched more easily compared to a plane, they provide tremendous opportunities for SSA economies.
Big Data and Cloud Deployment in Modern Versus Traditional Sectors
Nedbank teamed up with South Africa’s Intersect Technologies to develop a secure system based on digital certificates and push notifications. Users approve or deny transactions on phones by entering PINs.
However, financial institutions such as Nedbank might face fluctuations in demand. For example, the end of the month is a high transaction period, because that’s when employees are paid. Likewise, the end of the year and holiday shopping seasons face high demands.
The system scales up during high transaction periods and scales down in slower periods. Compared to the more traditional iCow application, Nedbank’s application is more costly. For example, digital certificates must be installed on the phone to authenticate transactions.
Key Driving Factors of Big Data and Cloud Industry and Market
The growth of SSA economies’ Big Data and cloud industry and the market is driven by a number of factors, which include government initiatives, local entrepreneurial activities, foreign multinationals’ entry into the region’s cloud sector, improving international bandwidth, international agencies’ roles, and philanthropic and charitable causes.
Governments in SSA economies are making efforts to strengthen the Big Data and cloud ecosystem. In May 2016, the government of Rwanda announced its plans to make government data accessible online in order allow interested parties to use them for business, research, education, and other purposes.
By doing so, Rwanda will be the fourth East African country after Kenya, Tanzania, and Uganda to have data portals. The National Institute of Statistics will implement the policy.
Rwanda has also a plan to build a US$1.9 billion innovation city in the Kigali Special Economic Zone. The city will comprise key elements of a typical urban center such as corporate buildings, retail, leisure, sports, accommodation, and a healthcare center.
Local Entrepreneurial Activities
Local entrepreneurial activities have helped cloud development. Innovation centers, such as Kenya’s iHub, have brought together software developers and entrepreneurs. South Africa’s Integr and MTN, and Zimbabwe’s Twenty Third Century Systems have launched cloud offerings in Sub- Saharan Africa.
MTN MyOffice supports accounting, human resource, CRM, email and video conferencing, storage and back- up for SMEs in manufacturing, hospitality, micro-finance, and advertising.
MTN Nigeria has developed a data center in Lagos with 500 m2 of collocation and hosting space. MTN offers cloud-based services to SMEs. Likewise, the Nigerian company Computer Warehouse Group (CWG) launched a Tier 3 data center in the country.
Note that Tier 3 facilities are often utilized by large businesses, which have 99.982 percent uptime, no longer than 1.6 hours of downtime per year and provide at least seventy-two-hour power outage protection.
In 2014, MainOne reportedly completed a US$40 million data center facility in Lagos. In 2014, Rack Centre completed a Tier 3 data center with 3,000 rack spaces.
MTN Nigeria, Globacom, Airtel Nigeria, and Etisalat Nigeria have also invested in data centers. These companies are deploying next-generation networks (NGN) and Business Intelligence (BI) software tools. For instance, Globacom was reported to spend US$1.25 billion to build an Internet Protocol (IP) network.
MTN is reported to spend over US$1 billion annually on its network. Likewise, Airtel and Etisalat spent over US$3 billion to improve their networks in order to make them useful for Big Data. As data volume expands, telecom operators can mine consumer data to enhance operational efficiency and increase revenue.
Sub-Saharan Africa’s international bandwidth has increased dramatically. For instance, during 2011–2015, Africa’s bandwidth capacity grew by 51 percent, which was higher than any other world regions.
In 2012, Kenya was connected to SEACOM, The East African Marine System (TEAMS), and East African Submarine Cable System (EASSy) cables, and its bandwidth increased from 20 to 53 GBPS from 2010 to 2011.
In Nigeria, Glo-1 was launched in 2009, and other cables in 2010 and 2012 broke Nitel’s SAT-3/WASC monopoly.
Telecommunications providers have made heavy investment to accelerate the diffusion of fiber Internet in Africa. The first phase of the African Coast to Europe (ACE) submarine communications cable started in 2012.
It is a 17,000 km-long fiber optic cable project, which aims to connect twenty- three countries.50 As of 2015, Mauritius- based Liquid Telecom was estimated to spend about US$500 million in more than 18,000 km of fiber cable in Africa.
In July 2015, China’s Huawei started work on a 4,000 km fiber optic cable project, which is expected to connect Guinea and other West African countries by 2017. The cable will have seventy-seven exchange points.
All these developments are likely to have a major impact on the use of Big Data and the cloud in SSA economies. SSA’s homegrown data center industry has been growing rapidly. Countries such as South Africa are reported to have some high-quality data centers.
The director of the Ugandan Internet eXchange Point noted that while it was more attractive to host SSA-oriented data services in Europe or North America than in Africa in the past, it is becoming increasingly attractive to host the services in Africa.
Philanthropic and Charitable Causes
Funding from philanthropic and charitable sources have also helped enrich the Big Data and cloud ecosystems. One notable example of such activities is Vital Signs, which is a system that provides near real-time data and diagnostic tools in order to help relevant stakeholders inform agricultural decisions and monitor outcomes.
The system was launched in Africa with a grant provided by the Bill & Melinda Gates Foundation to Conservation International. This program is launched in several SSA economies in order to collect and integrate data on agriculture, ecosystems, and human well-being.
As of early 2016, Vital Signs research teams began collecting data in Tanzania, Ghana, Kenya, Rwanda, and Uganda. Some of the researchers conduct household surveys that deal with diver topics, such as nutrition, farming practices, and collection of water and fuelwood.
Other researchers collect data on the landscape. For instance, soil samples are sent to Nairobi- based World Agroforestry Centre lab to analyze the composition and measure organic carbon contents.
The diameter, height, and canopy of trees are measured in order to calculate the amount of above-ground carbon held by forests.
Measurements from satellite imagery are used to study land- cover changes such as the conversion of forest to farmland. Using a tablet, Vital Signs researchers upload the information to a cloud-based data management and analysis system.
The raw data are then translated into indicators and maps for decision makers such as government agencies, civil society organizations, and farmer cooperatives.
Vital Signs and the Tanzania Ministry of Agriculture, Food Security and Cooperatives (MAFC) have formed a partnership to develop an implementation strategy for Climate Smart Agriculture (CSA).
Note that CSA is defined by the United Nations’ Food and Agriculture Organization (FAO) as agriculture that can lead to a reduction in greenhouse gas emissions (GHGs) and an increase in agricultural adaptation and productivity.
These measures can strengthen national food security and achieve various development goals.
A Low Degree of Digitization
In 2012, the Internet’s contribution to Africa’s GDP was estimated at 1.1 percent compared to emerging economies’ average of 1.9 percent and developed economies’ average of 3.7 percent.
A wide variation exists across SSA economies in the extent to which the Internet is helping economic growth. For instance, in Senegal and Kenya, the Internet was estimated to contribute 3.3 percent and 2.9 percent of GDP respectively.
The corresponding contributions in Ethiopia and Angola were 0.6 percent and 0.5 percent of GDP respectively.
Unsurprisingly, most SSA economies have been unable to realize the benefits of modern ICTs. For instance, being able to accurately count the number of children is the first step toward realizing the benefit of Big Data and the cloud in health care. Many SSA economies have a notoriously poor record, even in registering the children born.
Estimates suggest that only 44 percent of children under five years of age in SSA economies have been registered. The proportions are even lower in rural areas. In Eastern and Southern Africa, the proportion is reported to be 38 percent and it is estimated to be as low as 3 percent in Somalia.
Many people living in slums in countries such as Nigeria cannot provide birth certificates or utility bills required by banks. Financial institutions have imposed these oppressively burdensome requirements in order to prevent money laundering.
The adverse effects of low digitization are felt across all economic activities, for instance, due to the low digital- payment penetration, only cash payments are accepted in most transactions.
Consumers, banks, and governments in SSA economies thus suffer from the high costs associated with transactions on a cash basis. These include extra costs and inefficiencies that can result from manual acceptance of cash, record keeping, counting, storing, physical security, and transportation.
Regulatory and Human Resources
Regulatory barriers often act as an inhibitor in the diffusion of Big Data and the cloud in SSA economies. For instance, Liquid needed to negotiate for two years in order to receive the permits required for taking its cable South Africa’s Limpopo to Zimbabwe.
According to the Business Software Alliance, South Africa ranked twentieth out of twenty-four economies analyzed in 2013 in cloud-related regulations.
Other Sub-Saharan African economies are far behind. Only twenty- four countries were included in the study and South Africa was the only SSA economy included.
Other Sub- Saharan African economies were not ranked in the study but they are further behind. Sub-Saharan Africa economies thus must strengthen regulations and train human resources.
PRIVACY AND SECURITY ISSUES ASSOCIATED WITH Big Data AND THE CLOUD
Privacy and security issues associated with Big Data and the cloud have been a top concern for firms in developing as well as developed countries.
According to a study conducted by EMC in 2014, data loss and associated business downtime cost the global economy over US$1.7 trillion annually.
China alone is estimated to have more than 1.5 million hackers, who have created an underground industry of more than US$15 billion by exploiting security flaws in Big Data, the cloud, and the IoT.
Likewise, a study conducted by Compfix Data indicated that over 45 terabytes of data are lost every year in Kenya alone. The study also found that a company that experiences an outage of ten days or more due to data loss cannot fully recover and 50 percent of such companies go bankrupt.
Big Data and cloud security issues are related to a number of important organizational outcomes. For instance, cloud services in some countries are experiencing a negative country-of-origin effect due to security issues.
For instance, according to the 15th annual Business Climate Survey of the Amer can Chamber of Commerce in China conducted with companies operating in China (most of which were from the USA) (“AmCham China”), which was released in March 2013, only 10 percent considered using China-based cloud computing.
The respondents expressed concerns about data security. Twenty- six percent of the respondents stated that their proprietary data or trade secrets related to China operations had been stolen.
A top concern for consumers has been privacy and security practices of companies handling their data. For instance, online credit services in China that use Big Data analytics in extending loans are being accused of abusing personal data to collect debts.
Alibaba’s Ant Check Later, which allows users to delay payments and pay in installments, allegedly misused personal data.
Finally, it is important to compare the privacy and security issues associated with Big Data and the cloud in developing and industrialized countries.
In the industrialized world, cloud and Big Data users are becoming educated and are bringing more holistic perspectives to incorporate all the relevant issues that are important to them such as cost saving, productivity gain, security and privacy issues and, control over data.
They have also changed their behavior in response to changing perceptions of the benefits and risks and their potential and realized power. Over time, this may give venders a better assessment of clients’ needs and power, which may lead to an effective tailoring of services and improvements in privacy and security issues.
Such conditions are less likely to be found in developing countries due primarily to the newness of the cloud and Big Data.
Characteristics of Big Data and the Cloud in Relation to Security and Privacy
Security and Privacy Issues Associated with the Cloud
A significant gap remains between CSPs’ claims and users’ views of the cloud’s security, privacy, and transparency. The cloud industry’s response has been: “Clouds are more secure than whatever you’re using now.” But many users do not agree.
Issues such as security, privacy, and availability are among the topmost concerns in organizations’ cloud adoption decisions rather than the total cost of ownership.
Due primarily to concerns related to security, privacy, and confidentiality, critics have argued that its perceived costs may outweigh the benefits.
Organizations worry about hidden costs associated with security breaches or lawsuits tied to a data breach. Many businesses and consumers are cautious in using the clouds to store high- value or sensitive data and information.
Security and Privacy Issues Associated with Big Data
The various characteristics or dimensions of Big Data For instance, in order to create highly customized offerings, a company may need to mine a huge amount (volume) of structured and unstructured (variety) data from multiple sources (complexity).
In some cases, this process may also involve the use of high-velocity data. Big Data may challenge the Fair Information Practices (FIPs).
If consumer data is not handled appropriately by organizations, in addition to privacy and CS issues, there are also possibilities of civil rights violations such as discrimination.
For this reason, regulators such as the Federal Trade Commission (FTC) are showing concerns that Big Data may “perpetuate and even amplify” societal biases by screening out certain groups, often disadvantaged ones, from opportunities for employment, credit, or other forms of advancement.
Developing world-based organizations are experiencing a huge amount of data flows from various sources.
For instance, Etisalat’s operating brand, Mobily, in Saudi Arabia noted that 1.3 petabytes of data flow daily through the company’s network. Organizations such as Etisalat are often required to store all data in one location in order to facilitate analysis.
The higher volume and concentration of data make a more appealing target for hackers. Moreover, a higher data volume increases the probability that the data files and documents may contain inherently valuable and sensitive information. Information stored for the purpose of Big Data analytics is thus a potential goldmine for cybercriminals.
A huge amount of data means that security breaches and privacy violations are likely to lead to more severe consequences and losses via reputational damage, legal liability, ethical harms, and other issues, which is also referred to as an amplified technical impact.
The availability of a huge amount of data also increases the possibility that personal data can be put to new uses to create value. The US FTC Commissioner pointed out the possibility that firms, “without our knowledge or consent, can amass large amounts of private information about people to use for purposes we don’t expect or understand.” Such uses often violate the transparency principle of FIPs.
A huge data volume is also related to the demand or even the necessity of outsourcing. An issue of more pressing concern is determining relevance within large data volumes and how to use analytics to create value from relevant data. Firms may thus rely on CSPs for analytic solutions.
The quickly degrading quality of real-time data is noteworthy. In particular, clickstream data (click paths), which constitute the route chosen by visitors when they click/navigate through a site, is typically collected by online advertisers, retailers, and ISPs.
The fact that such data can be collected, stored, and reused indefinitely poses significant privacy risks. Some tracking tools can manipulate clickstreams to build a detailed database of personal profiles in order to target Internet advertising.
An important use of Big Data is real-time consumer profile-driven campaigns such as serving customized ads. For instance, location- tracking technologies allow marketers to serve SMS and other forms of ads based on real-time location. This process often involves passive data collection without any overt consumer interaction.
The lack of individual consent for the collection, use, and dissemination of such information means that such a practice violates the individual participation principle of FIPs.
Big Data initiatives have led to an increase in both the supply and demand of location-based real-time personal information. Data created and made available for use in the implementation of Big Data initiatives also have negative spillover effects. Particularly, the availability of location information to third parties may have some dangerous aspects.
One example is the use of location data for stalking people in real-time. For instance, the iOS app Girls Around Me, which was developed by the Russian company I-Free, leveraged data from Foursquare to scan and detect women checking into a user’s neighborhood.
The user could identify a woman he liked to talk, connect with her through Facebook, see her full name, profile photos, and also send her a message. The woman being tracked however would have no idea that someone was “snooping” on her. As of March 2012, the app had been downloaded over 70,000 times.
There is also a physical risk of (near) real-time data. For instance, a China Daily article commented that in China, illegal companies buy databases from malicious actors and provide services to their clients, which include private investigation, illegal debt collection, asset investigation, and even kidnapping.
By combining structured and unstructured data from multiple sources, firms can uncover hidden connections between seemingly unrelated pieces of data. In addition to the amount, a high variety of information in Big Data makes it more difficult to detect security breaches, react appropriately, and respond to attacks.
One estimate suggested that only about 10 percent of available data is in a structured form (e.g., transactional data on customers, time-series data from statistical agencies on various macroeconomic and financial indicators) which can be presented in rows and columns.
Especially because of the relative newness, most organizations lack the capability to manage unstructured data, which arguably contains more sensitive information.
Processes and technology solutions for securing unstructured data are still in the nascent phase and governance issues are not addressed.
For instance, organizations often lack mechanisms to ensure that permanent and temporary employees and third parties have appropriate access to unstructured data and that they are in compliance with data protection regulations.
According to a survey released in 2013 by Ernst & Young Global Limited, which was conducted among Indian firms, 43 percent of the respondents were concerned about data privacy and the security risks associated with the handling of unstructured data as among the major challenges.
The variability characteristic is related to the time-variant nature of security and privacy risks. The volume of data collected and stored, which need protection, will grow during the peak data collection and flow periods.
It is during such periods that organizations may lack the internal capacity and tools to manage and protect information. A related point is that the attractiveness as a prime target is high during such periods.
The variability characteristic of Big Data may also necessitate the outsourcing of hardware, software, and business-critical applications to CSPs.
Applications such as ERP and accounting systems are required to be configured for peak loads during daily and seasonal business periods or when quarterly and annual financial statements are prepared.
Big Data often constitutes aggregated data from various sources that are not necessarily identifiable. There is thus no process to request the consent of a person for the resulting data, which is often more personal than the set of data the person would consent to give. A related privacy risk involves re-identification.
It is possible to use a data aggregation process to convert semi-anonymous or certain personally non-identifiable information into non-anonymous or personally identifiable information.
Health-related data is of special concern. Based on a consumer’s search terms for disease symptoms, online purchases of medical supplies, and RFID tagging of drug packages can provide marketers with information about the consumer’s health.
Access to such information would enable an insurance underwriter to predict certain disease and disorder probabilities, which would not be possible using information voluntarily disclosed by consumers.
Many of the innovations involving Big Data use multiple data sources and involve transferring data to third parties.
Many organizations believe that making data anonymous before sharing with third parties would make it impossible to identify. This is often a convenient but possibly false assumption.
Researchers have presented a variety of methods and techniques that can be used to de-identify personal data and reassociate with specific consumers. Big Data processes can generate predictive models that have a high probability of revealing PII40 and thus make anonymization impossible.
Failure to protect PII and unintended or inappropriate disclosure violate the security provision of FIPs. In some cases, the identified person may suffer physical, psychological, or economic harm.
The Security and Privacy Situation in Developing Countries in the Context of Big Data and the Cloud
Most of the current discussion on Big Data and the cloud in relation to security and privacy has been focused on industrialized countries.
One commentator noted that about 90 percent of the discussion at the 2013 Internet Governance Forum (IGF ) held in Bali, Indonesia referred to Big Data as a surveillance tool.
At the same time, the debate focusing on developing countries treated Big Data as a means to observe people to fight poverty.
The argument provided by IGF participants was that data can help provide access to clean drinking water, health care, and other necessities. Some have challenged this view and noted that poor people have no less reason than rich people to be worried about surveillance.
Privacy violation is most likely to occur in countries with poor protection of civil liberties. The worst case is that the authoritarian government may see and use detailed, real-time data on citizens.
However, due to the secrecy in the way information is handled, the affected individuals may not have a way to know that their information is inappropriately accessed and used.
Likewise, some businesses may obtain, use, and sell personal data for their own gain. There may not be any restrictions on such activities and people whose information is used or sold may lack control over how their personal data is handled.
CS and privacy issues in developing countries need to be seen in the backdrop of the rapid diffusion of modern technologies such as the IoT. Banks and retailers are using customers’ real-time geo-location technologies for authentication and other purposes.
New types of biometric data such as fingerprints, iris scans, voice-recognition software, and facial recognition are also being used for authentication.
Location and financial data and other information can be attacked by cybercriminals. Such new developments require new security measures and user authentication to make sure that customers are happy and transmitted data is secure.
It is important for users to understand that they can fully trust the connected devices that are tied to bank accounts.
Most developing world-based organizations which collect consumer data perform extremely poorly in protecting privacy. Consider the 2015 Corporate Accountability Index of the Washington DC-based non-profit research initiative, Ranking Digital Rights.
With regard to user privacy, Tencent ranked thirteen out of the sixteen tech companies surveyed.
The survey did not include Baidu and Alibaba. The companies included in the survey were evaluated using a number of criteria such as the existence of privacy policies, how user information is collected and shared, and security practices.
Measures Taken at Various Levels to Strengthen Security and Privacy in Developing Countries International organizations, governments, NGOs, and private sector actors in developing countries are directing more efforts towards strengthening data privacy and CS issues.
A 2016 survey by the UN Conference on Trade and Development found that more than half of all developing countries still lacked national legislation to protect data and privacy online. In addition, many countries have legislation that needs to be updated and/or better enforced.
There is no globally accepted instrument to address the concerns related to data protection and privacy.
The current system for data protection is highly fragmented, with diverging global, regional, and national regulatory approaches. At the same time, various measures are being taken at the international level to address this situation.
For instance, the African Union Convention on Cyber Security and Personal Data Protection requires member states to establish a legal framework for the “protection of physical data and national Data Protection Authorities” (DPAs).
Other regional initiatives include agreements by the European Union, the Asia-Pacific Economic Cooperation and the Commonwealth.
At the global level, the Council of Europe Data Protection Convention of 1981 (“Convention 108”) is the most prominent binding international agreement on data protection.
As a response to domestic and international pressures to build CS measures, in July 2013, the Government of India released the National Cyber Security Policy (NCSP). The NCSP outlines the basic policies and strategies “to build a secure and resilient cyberspace for citizens, businesses and government.”
It set forth fourteen objectives that included enhancing the protection of critical infrastructure and developing 500,000 skilled CS professionals in the next five years. The development of public-private partnership (PPP) efforts towards enhancing the CS is a key component of the NCSP.
Note that PPPs are especially well-suited and justified for areas that require diverse types of expertise and knowledge in order to address complex problems. This condition fits squarely with CS.
Professional and Trade Associations
As important sources that shape institutional structures in an economy, professional and trade associations play significant roles in bringing and legitimating institutional changes in the areas of security and privacy in Big Data and the cloud environments.
In order to understand professional and trade associations’ roles in shaping a nascent industry in a developing economy (e.g., Big Data and the cloud), it is important to examine such associations in relation to other institutional ele-ments—most notably, the state.
Note that the state is arguably the most important institutional actor. With regard to the state’s role in influencing industry behavior in emerging economies, however, it is important to note that the rule of law is “often weakly developed” or sometimes “ignored with impunity” in such economies.
Second, in the nascent and formative sectors such as Big Data and the cloud, there is no developed network of regulatory agencies comparable to established industrial sectors. In such settings, professional and trade associations may emerge to play unique and important roles in shaping the industry.
India’s Data Security Council of India (DSCI), an industry body, entered into a partnership with Pearson VUE to deliver a data privacy credentialing program: DSCI Certified Privacy Professional (DCPP).
The certification is expected to address the need for privacy professionals in the country. DCPP equips individuals with the necessary privacy-related skill sets.
Individuals with the DCPP certification will be aware of privacy-related concepts and principles and the data privacy landscape in India and other economies. They will also learn about contemporary global developments in privacy-related matters, data protection regulations, and trans-border data flows.
In India, a report by the Internet & Mobile Association of India (IAMAI), a not-for-profit industry body, argued against a mandatory requirement to set up data centers in India.
It maintained that data location requirement is likely to harm Indian companies. The report cited many examples of Indian companies that rely on international data centers.
For instance, Zoho’s data centers are in California and New Jersey. Myntra and Redbus host servers with CSPs such as AWS. Likewise, in the beginning, Flipkart relied on data centers in Canada.
In some countries, Internet companies are directing more efforts towards strengthening CS. In China, an e-commerce union has been formed, whose members comprise of major online firms. The union analyses vendor data such as those related to transactions and other sales activity in order to identify rogue online vendors.
Providers of Big Data and the Cloud
Developing world-based providers of Big Data and the cloud is taking measures to strengthen security. For instance, as of 2014, China’s Aliyun was reported to have a 100-plus personnel team to provide cloud security.
Organizations and Consumers Using Big Data and the Cloud
CIOs are increasing their orientation towards security and privacy. According to a survey released in 2013 by Ernst & Young Global Limited, which was conducted among Indian firms, 69 percent of respondents were planning to strengthen CS.
Likewise, as noted earlier, China Youth Daily’s poll showed that over three-quarters of respondents believed there was an abuse of Big Data.
The examples related to the attacks on Aramco and RasGas are illustrative of a widespread problem not only in GCC economies but also in all other economies, including developing economies.
Organizations and consumers in developing countries face unique risks and challenges related to privacy and security in the Big Data and cloud environments.
Despite some initiatives, limited international cooperation on privacy and security issues exists among developing countries.
For instance, while the African Union (AU) adopted its Convention on Cybersecurity and Personal Data Protection in 2014, only eight of the fifty- four members of the AU had signed the Convention as of July 2016. By that time, no country had ratified the Convention.
The actions of Etisalat and many other companies involved in handling personal data indicate that the lack of privacy and security is often the product of the thoughtless and indifferent attitudes of these companies towards these issues.
There thus remains a notable lack of institutionalization of privacy and security issues among most firms handling consumer data in developing countries.
From the privacy and security standpoint, Big Data and the cloud are likely to affect the welfare of unsophisticated, vulnerable, and technologically unsavvy consumers more negatively.
Such consumers may lack awareness of multiple information sources and are less likely to receive up-to-date and accurate information about multiple suppliers in a manner that facilitates effective search and comparisons.
They are also not in a position to assess the degree of sensitiveness of their online actions and are more likely to be tricked by illicit actors. Consumers in developing countries are more likely than those in developed countries to exhibit these features and profiles.
Big Data and Cloud Computing in Key Development Areas in the Global South
Primary sectors remain dominant in most LDCs. This sector, however, is a laggard sector in the adoption of new technologies. For instance, according to Wolfgang von Loeper, a former farmer, and the founder of the MySmartFarm app, the average African smallholder farmer produces only a quarter to half of the productive potential.
This low productivity of smallholder farmers is attributable to their low rate of adoption of modern technologies.
For instance, the Indian Big Data and cloud market for agriculture—despite some signs of progress— remains relatively backward compared to some other developing countries. The agricultural sector in India has not received the attention that it needs and deserves.
For instance, fruits and vegetables worth US$2 billion are wasted annually in India due to the lack of supply chain management and cold storage facilities. The agricultural sector is characterized by extremely low investments in modern ICTs.
For instance, in 2015, US$6 billion was invested in tech start-ups, of which agriculture start-ups attracted less than 1 percent of the total.
Several benefits have been identified that Big Data and the cloud can offer to the primary sector. For instance, just like in computer chips and other sophisticated industries, sensors in primary industries such as agriculture, oil and gas, and pulp and paper can be used to take detailed readings on process conditions.
Based on the readings, automatic adjustments can be made in order to reduce waste, downtime, and human interventions. According to Monsanto, the world’s biggest seed company, tailoring information and advice to farmers could increase annual worldwide crop production by about US$20 billion.
In the oil and gas sector, conditions of machines and equipment can be monitored, which can result in more effective maintenance and inspection based on industry as well as historical and real-time data.
Early warnings from sensor data can help replace planned maintenance with preventive maintenance, which can reduce downtime. Instant information from oil wells can provide information to make timely decisions on underperforming wells.
Detection of anomalies while drilling as well as during operation can lead to more effective decisions for cost savings.
Nonetheless, the transformative potential of Big Data and the cloud has not yet been realized in the primary sectors. For instance, an observation is that the oil and gas industry is not among the early adopters of digital technologies. BCG’s Grant McCabe, who is the team leader for “next-generation mining” noted: “There is enormous slack in many mining systems.
Surveying of potential oil drilling sites involves monitoring seismic waves moving through the earth. At a spot being surveyed, the patterns are examined to see if the waves are distorted as they pass through oil or gas.
In the past, a few thousand readings were taken at a potential drilling site. Advancements in Big Data analytics and other technologies have made it possible to increase the number of readings to more than one million.
This increases the accuracy of images of sites. Shell uses fiber optic cables to analyze the data generated by sensors. The data is transferred to its cloud servers, maintained by AWS.
Data from a potential oil field is compared with thousands of other sites around the world in order make more accurate recommendations regarding the sites to drill. Production forecasting, which entails estimating the likely output of a reservoir, determines the resources that should be spent on collecting it.
Data- led decisions to allow operators to have more confidence regarding the efficiency with which oil can be extracted. Shell also uses Big Data to ensure that machines are working properly, which minimizes breakdowns and failure.
This is especially important as oil drilling machines operate in adverse conditions for long periods of time, which increases the probability of wear and damage. The machines are fitted with sensors, which collect data about various performance indicators.
Some Big Data- and Cloud-Based Applications in the Primary Sector
A number of different Big Data- and cloud-based applications have been developed and deployed in the primary sector of developing countries.
As noted above, tools such as Maine's “Enterprise Knowledge Graph” allows data analysts, business analysts, data scientists, and enterprise architects in an organization to collaborate.
Apps have also been developed for the forestry and fishing sector. Global Fishing Watch uses data and mapping to deal with environmental problems such as deforestation, illegal waste dumping, and oil spills.
The Pew Charitable Trust’s Eyes on the Seas project combines satellite data, fishing vessel, and other information to help authorities monitor fishing activity.
Likewise, Global Forest Watch uses a wide variety of data to spot illegal logging or other activities that damage forest resources. Public platforms such as Global Fishing Watch enable anyone to act as a watchdog and to report environmental crimes.
Such activities can press companies to engage in appropriate behavior and governments to pass and enforce environmental laws.
NGO Oceana, the non- profit environmental mapping service SkyTruth, and Google have teamed up to develop the Global Fishing Watch public platform, which shows the location of fishing vessels.
By checking AIS data used in tracking ships and vessel traffic services, it can be ensured that fishing ships do not enter banned or restricted areas.
The data can be used to improve knowledge about illegal fishing. According to the United States National Oceanic and Atmospheric Administration, 40 percent of the catch in some fisheries are illegal, unreported, or unregulated (IUU).
While activist organizations such as Global Fishing Watch are taking initiatives to track environmental offenses, they face a number of difficulties. For instance, vessels may turn off their AIS transmitters.
Buyers, however, could force fishing companies to become more compliant by insisting that their fish comes from vessels that have their transmitters operational at all times, thus being transparent about where they are fishing.
Key Driving Forces in the Adoption of Big Data- and Cloud-Based Applications in the Primary Sectors
A number of forces have come together to drive the adoption of Big Data and the cloud in the primary sector.
Relevant Policy- and Decision-Makers’ Interest in Big Data and the Cloud
Developing countries’ policy and decision makers in primary sectors have put Big Data and the cloud high on their organizational and national developmental agenda. They are gaining a better understanding of the transformative potential of Big Data and the cloud.
For instance, according to the above-noted study conducted by DNV GL in the UAE, over half of senior oil and gas professionals in the country saw Big Data’s high potential to transform the operating efficiency of the industry.
In order to improve efficiency in the mining industry, Kazakhstan signed a deal with Google and McKinsey to utilize Big Data in the industry. Kazakhstan wants to become a pioneer in the Big Data deployment to improve the efficiency of the country’s mines.
Kazakhstan has established a “mining industry competence center,” which gathers data from sensors within mining and processing equipment located in different parts of the country. The use of real-time data allows companies in the industry to identify bottlenecks and improve efficiency.
Big Data- and Cloud-Related Investments in the Primary Sector
Investments in Big Data and cloud technologies are flowing from the public as well as private sectors. For instance, India’s meteorology office uses a statistical method introduced in the 1920s under the British colonial rule.
In June 2016, India announced a plan to spend US$60 million on a new supercomputer system in order to improve the accuracy of weather forecasts.
The new system generates three-dimensional models to predict the monsoon’s development. Some experts think that better forecasting could help India boost farm output by as much as 15 percent by helping farmers make decisions regarding the best time to sow, irrigate, or apply fertilizer.
“Enterprise Knowledge Graph,” data analysts, business analysts, data scientists, and enterprise architects in an organization can collaborate in a single, integrated system.
The Roles of the Transnational Corporations (TNCs)
In one way, transnational corporations (TNCs) are likely to be a driving force behind the diffusion of cloud and Big Data in the primary sector of developing countries.
For instance, large food and biotechnology TNCs such as Monsanto and Syngenta already have a notable presence in developing countries, which is a positive factor from the standpoint of Big Data led productivity growth in these countries.
During 2005–2007, the share of agriculture in FDI inflows was 15.1 percent in Cambodia and 12 percent in Laos.
Monsanto reportedly has control on over 95 percent of the Indian cotton seed market. TNCs, which are often producers, processors, or traders of agricultural products or sellers of inputs or machinery, engage in a contracting system in which they assume a variety of responsibilities including providing technical assistance and marketing to developing world-based small farmers.
NCs such as Monsanto and Syngenta, which have become a driving force behind the utilization of Big Data in the industrialized world, are thus likely to act as a key channel in the international technology transfer of Big Data.
A typical offshore oil production platform is estimated to have over 40,000 data tags. However, not all of them are connected or used.
In order to convert to making better business and operating decisions using the datasets, new and carefully designed capabilities for data manipulation, analysis, and presentation are required. In addition, tools to support decision- making are needed.
One estimate suggested that if production efficiency of a brownfield oil and gas service company is improved by 10 percent, profitability will increase in the US$220 million to US$260 million range.
Digitization can also extend field life. Even higher potential could be achieved in greenfield assets by including instrumentation from the start.
Global technology providers have become an even more important force in driving the adoption of Big Data and cloud in the primary sectors in the developing world. In mid-2016, Microsoft opened its biggest center of excellence for the oil and gas industry in Dubai.
The center seeks to help organizations in the oil and gas sector to utilize the latest technologies such as the IoT, Big Data analytics, and cloud computing using Microsoft Azure and Office 365.
The Roles of International Agencies
In some countries, international agencies have been the driving force behind the adoption of Big Data and the cloud.
For instance, Haiti’s Ministry of Agriculture has strengthened its knowledge management system through its adoption of cloud technology. This project is funded by the World Bank and makes Haiti’s agricultural infrastructure, which was destroyed by an earthquake in 2010, resilient to natural disasters.
Some encouraging signs have emerged to suggest that the adoption of Big Data and the cloud are likely to get a big boost in the primary sectors of some developing countries.
Among the most encouraging factors is the rapid increase in investment in this sector. For instance, as noted earlier, agtech is one of the sweet spots for VC investors.
The VC investments are likely to lead to the development of technologies that are likely to benefit smallholder farmers. As noted above, policy and decision makers in these sectors are gaining a better understanding of the transformative potential of Big Data and the cloud.
EDUCATION AND R&D
In recent years, this trend has changed. According to Markets and Markets, the global cloud computing market in education will grow from US$5.05 billion in 2014 to US$12.38 billion by 2019.
Big Data and the cloud are playing the central role in R&D and educational system in developing countries.
For instance, South Korea’s Ministry of Education, Science and Technology are implementing a program that will turn the nation’s classrooms paperless by 2015. This program will provide each student with a tablet and access to textbooks and other educational materials from a cloud computing system.
Before proceeding further, it is important to note that the conventional learning environments suffer from several limitations such as the lack of immediate feedback to students, the requirement for teachers to spend many hours grading routine assignments, and failure to take advantage of digital resources in order to improve the learning process.
A complaint that is often made is also that there are a number of drawbacks in the system of recruiting, training, supervising, and monitoring teachers in developing countries.
There is arguably the lack of proactivity of teachers to show students how to improve comprehension. It is also argued that the education system is mainly input driven.
The management of the education system at best focuses exclusively on logistical targets such as money spent and construction of schools. There is often no environment to provide support or incentives to produce high learning achievement.
Other challenges that have affected the quality of education in developing counties include a high rate of teacher absenteeism, the role of political patronage in the hiring of teachers, low technical quality, and the ineffectiveness of teacher training.
The upshot of these tendencies is that a large proportion of children and youths in developing countries are deprived of educational opportunities. For instance, in Africa, thirty million children fail to attend primary school education.
Some of the above-mentioned problems can be addressed by Big Data- and cloud-based learning solutions. For instance, Bridge International Academy, which provides e-learning solutions claimed that its tools have reduced unexcused teacher absenteeism to less than 1 percent. Technology use would lead to better monitoring and control.
If a teacher fails to sign into the tablet, Bridge can call the teacher to find out the reason. Data-driven approaches make it possible to analyze learning in real-time and offer systematic feedback to students as well as to teachers.
Big Data and the cloud have also facilitated R&D activities in developing countries. For instance, thanks to the cloud, it has been possible to have supercomputer power to access educational resources and to analyze data on disease spread pattern and climate changes. Likewise, Yahoo! has collaborated with the Indian Institute of Technology Madras (IIT-Madras).
It established a Grid Computing Lab, which allows researchers to access and conduct research on Big Data and cloud computing.
To take another example, scientists at University of Washington’s Center for Infectious Disease Research and India’s Goa Medical College used cloud computing and Big Data to conduct research into factors that make some malaria cases severe and life-threatening.
The research team analyzed data on sixty patients using advanced computing techniques to find relevant patterns. The project analyzed fifty parasite binding proteins and additional variables for each of the patients. Finding patterns in a large number of variables required the use of machine learning and other computing techniques.
Big Data- and Cloud-Based E-Learning Tools and Systems
Imported as well as locally developed Big Data- and cloud-based e-learning tools and systems are rapidly transforming developing countries’ educational landscapes.
Big Data and the cloud are being deployed at all levels of educational situations. In this section, we briefly review some of the e-learning tools and the organizations involved in developing them.
BRCK’s Kio Kit and Kio Tablets
The system was designed in Kenya and is equipped with a sim card and Internet connectivity. However, when the devices are provided to students, they are not connected to the Internet, which means that students cannot look at non-educational contents. New materials can be updated on the tablets when they are connected to BRCK.
The Kio Kit houses a web server also referred to as “micro-cloud,” which is an offline version of the Internet. It provides rich, interactive content available on the web but users do not need to pay expensive data costs.
The Kio Kit is encased in a tough, water-resistant plastic container, which also acts as a charger when the tablets are stored. The whole unit can also be charged from a wall outlet, solar power, or a car battery.
The seven-inch Kio tablet is breakproof for up to a 70 cm drop on a concrete floor. It can also survive occasional water spills and dust exposure. It has a scratch resistant screen coating and rubber outer shell.
BRCK Kio Kit won the Stuff Magazine’s “Educational Tech of the Year” Award for its innovative design.
New materials are uploaded on the BRCK wirelessly during the night when more bandwidth is available. The materials are then shared with the tablets during classes.
A teacher thus can take the Kio Kit home and download the lessons for the next day if there is no connectivity in the school. In remote areas that lack Internet access or where Internet access is expensive, updates are made by a technician in person.
As of 2014, Bridge International offered three years of early childhood education, and seven years of primary education (Classes 1–7). Bridge utilizes Big Data, algorithms, and a scripted-learning education methodology. Bridge was opened in Kenya in 2008.
As of September 2015, Bridge served about 120,000 students. It has a huge amount of data on its students. The longitudinal data on children capture their developmental process.
Thanks to the value and insights provided by the data, Kenya’s Ministry of Education was reported to be reconsidering the regulatory framework. The goal is to reach 10 million children by 2025.
Bridge opened a London office in 2015. The bridge was awarded WISE Awards for innovation in education. WISE inspires girls and women to study and build careers in science, technology, engineering, and mathematics (STEM).
In 2015, an Indian expansion team was founded. It was reported that Bridge expressed an interest in partnering with the Andhra Pradesh government. Bridge’s plan was to launch in India in the 2016/2017 academic year.
In March 2016, the Liberian education minister announced that the country's entire pre-primary and primary education system would be outsourced to Bridge.
Under the public-private arrangement, Bridge would pilot the program in fifty public schools in 2016 and design curriculum materials. Phase two involves the rollout of mass implementation over five years.
The Internet and Barnes & Noble’s Nook tablets are used to deliver lesson plans. Teachers are provided with tablets, which are used for instruction, assessment, and data- gathering. The tablets are used to collect test results from students, which serve as a means of monitoring progress.
Teachers check-in via their tablets when they arrive. They run lessons almost verbatim from the tablet’s scripts, which are data-driven.
The data is compiled and analyzed at Bridge’s Nairobi offices and Massachusetts-based headquarters. Bridge argues that the use of technology and standardized procedures enhance the quality of education it offers.
It has attracted diverse investors. The California-based venture-capital firm Learn Capital LLC is Bridge’s largest shareholder in with a 15 percent stake. The bridge has a plan to seek a stock market listing in NSE in 2017. In March 2015, Facebook co-founder Zuckerberg invested US$10 million in Bridge.
In 2014, the IFC announced an investment of US$10 million in equity to support the expansion of Bridge. The UK’s development finance institution CDC also announced its plan to invest US$6 million in equity. The goal was to support the company’s plans to expand to more African countries.
Bridge uses technology and data to manage non- instructional activities such as billing, payments, expense management, payroll processing, and prospective admissions, which leads to a reduction in overhead costs to run an academy.
These activities are automated and centralized through the Academy Manager’s smartphone application and the Teachers’ tablet application.
A Bridge Inter-national Academy has only one employee in management: the Academy Manager (the “principal”).
Bridge argues that a high degree of digitization means that the Academy Manager can focus on more critical works that must be executed locally such as overseeing classroom instruction and managing relationships with parents and the local community.
It was reported in 2014 that the company was developing software, which analyzes previous test scores and levels of participation so that teachers know the students that need to be called on for a specific question. In this way, the system is output rather than input focused.
Bridge also ensures 100 percent teacher attendance with a pool of on-call substitutes and other measures. Note that in Kenya, teachers have an absenteeism rate of 47.3 percent in government schools and more than 30 percent in private schools. Bridge charges a tuition fee of US$6 a month. It does not accept cash. Parents can pay by smartphone.
DreamBox uses game technologies and immersive math courseware in order to make learning more fun and interesting. Algorithms adapt the learning experience to a student’s needs.
Brilliant | Math and science done right make it possible for talented students in mathematics and physics to learn at their own speed. Its global massive online open courses (MOOCs) use social networks, videos, and community interactions to offer university-level classes.
Eneza Education has developed a mobile platform, which utilizes Big Data and the cloud to offer students access to quizzes, mini-lessons, and other educational contents.45 For instance, a student who wants to take a math quiz texts a code. The system texts back the student with math topics based on the national curriculum.
The student selects the topic and is then texted back with five multiple-choice questions. After the student finishes the quiz, the system provides feedback on the answers. Eneza also allows users to search Wikipedia using SMS. Students can also ask a teacher questions. Teachers can monitor their students’ performance through their accounts.
Schools can pay US$180 annually to have access to student data and teaching resources. Parents can get similar accounts for about US$15/year. Using the Eneza platform, students, teachers, parents, and school leaders can communicate with each other.
As of mid- 2015, Eneza had more than 300,000 students from over 700 schools in Kenya and over twenty schools had subscribed its data. By early 2016, Eneza was operating in Kenya, Tanzania, and Ghana and it plans to launch in Nigeria and South Africa in 2017.
Some of the key challenges faced by Eneza in rural areas include the lack of devices and the difficulties of establishing and maintaining relationships with mobile network operators.
As of 2013, thanks to a partnership with Safaricom, the cost of taking a five-question test was three Kenyan shillings (about US$0.03). Before the partnership, the cost was twenty Kenyan shillings (about US$0.23).
Eneza wants to reduce the costs of its services to students. The company is developing other revenue streams such as selling data via subscription to schools, the government, and other stakeholders, interested in knowing students’ performance.
Coursera is a MOOC platform, which provides cloud-based education by offering courses in science, math, medicine, and other areas. The goal is to help students gain market-relevant IT skills.
The World Bank’s New Economy Skills for Africa Program (NESAP- ICT) and Tanzania’s Commission for Science and Technology (COSTECH) partnered with Coursera to launch an initiative to incorporate Coursera offerings to pilot the Youth Employment Accelerator Program Initiative (YEAPI).
In 2013, as part of its Global Learning Hubs program, the US Department of State’s Bureau of Educational and Cultural Affairs facilitated discussion to offer Coursera courses on a number of subjects in over thirty countries including China, India, Tunisia, Georgia, and Bolivia.
In June 2016, Coursera and the Indian School of Business (ISB) announced the launch of four courses on “Financial Markets and Investment Strategy.” The ISB had offered on Coursera’s MOOCs platform for the first time in 2014.
As of 2015, 40 percent of students who took Coursera classes were from emerging economies, which included 9 percent from Latin America and 4 percent from Africa.
Advance Learning Interactive Systems Online (ALISON)
ALISON provides cloud-based learning solutions. As of mid-2016, ALISON had 1.5 million users in Africa, and half a million were active every month.54 ALISON earns about 60 percent of revenue through certification and 40 percent by advertising.
In order to address the skills gaps, the Mountain View, California- based online education company Udacity works with companies such as Google, Facebook, Amazon, Github, and Cloudera to design courses.
It does not considtra ditionalnal universities as a model. Most of Udacity’s courses were created with at least one company’s help. Companies also offer material as well as experts to help build courses and provide internship opportunities for students.
They also give Udacity funding and resources. For example, Google gave Udacity US$4 million to create its Android Nanodegree program, which teaches “tools, principles, and patterns that underlie all Android development.”
Udacity entered into India in 2015. As of mid- 2015, India was Udacity’s second largest market in terms of the number of students. The company was enrolling at least 27,000 students in India every month.
India’s Flipkart has a partnership with Udacity to hire graduates based on capabilities built through, Nanodegree program. In 2016, Flipkart hired three students without in-person interviews based on their Nanodegree projects and Udacity profiles.
Big Data and Cloud Computing in R&D
A number of notable observations are reported regarding the use of Big Data and the cloud in R&D activities.
As we have seen above in this blog and in earlier blogs, Big Data and the cloud have strongly stimulated and facilitated R&D in the developing world. Here we briefly illustrate and summarize the use of Big Data and the cloud in two key developing countries: Brazil and South Africa.
Brazil’s universities and research institutes are using the public as well as private cloud services. As of 2015, the Brazilian research and education network Rede Nacional de Ensino e Pesquisa (RNP), which is Brazil’s academic Internet backbone, connected about 350 public and private universities and research institutions through a national backbone.
RNP’s data center also hosts its partner institutions’ applications including a web portal offering access to a large number of international scientific journals.
Thanks to South Africa’s significant investment in cyberinfrastructure, the country’s researchers are increasingly using high-performance computing for research and education. The Centre for High-Performance Computing (CHPC) was established in 2007 by the South Africa Department of Science and Technology (DST).
The CHPC’s Big Data-related activities include providing training to data scientists, supporting research projects using Big Data, and facilitating researchers’ participation and collaboration with international networks.
The South African Research Network (SANReN) provides cyberinfrastructure for Big Data to South African universities. In collaboration with the Tertiary Education Research Network of South Africa (TENET), the SANReN has connected South African universities to fiber-based cyberinfrastructure.
A number of organizations have been established to deploy Big Data in research activities. The Nelson Mandela Metropolitan University launched the new Centre for Broadband Communication in order to conduct research around fiber optic data transport for the SKA.
Also, the Consortium for Advanced Research Training in Africa has worked with Google to develop a virtual research platform, letting nine university partners, four research institutes, and eight partners in North America, Europe, and Australia collaborate on research, manage application processes, submit online assignments, attend webinars, and participate in discussion forums.
Medical research is being combined into huge searchable databases, which make it easier to assess and compare results.
By looking at databases with related prescription dosages, environmental patterns, and age-related trends, physicians can accurately pinpoint the most likely causes of a health problem such as drug, weather, and humidity, or animal migration patterns.
Key Drivers of Big Data and Cloud Deployment in E-Learning and R&D
A number of forces and trends have given rise to a rapid deployment of Big Data and the cloud in e-learning and R&D activities. Here, we discuss some of the key driving factors.
Some governments have launched programs to facilitate access to Big Data- and cloud-based education to the broader public. One such program is Rwanda’s one digital ID per child program. The goal of the program is to provide access to digital education content via Office 365.
Local Innovations and Entrepreneurial Efforts
Local entrepreneurial firms have been among the driving forces behind the digitization of educational activities in developing countries. BRCK is a high-profile example of a successful technology firm focusing on the education sector based in developing countries. BRCK is one of the first consumer electronics companies in Kenya.
As of 2015, BRCK had sold over 2,500 devices in fifty-four countries. As of March 2016, Kio Kits had been sold in schools in Kenya, Tanzania, and the Solomon Islands. There were also orders coming in from Sudan.
Transnational Companies’ Efforts
Multinational companies’ efforts correlate with the development and deployment of Big Data and the cloud in R&D and educational activities in the developing world. In April 2016, Google announced its plan and commitment to training one million Africans in digital skills.
Google supports Livity Africa to run two training programs: (1) Digify Bytes aims to provide young people with digital skills; and (2) Digify Pro is a three- month program aimed at digital specialists.
As of April 2016, the programs had been launched in Nigeria, Kenya, and South Africa. Google has also launched Home, which is an online-learning portal containing a wide range of digital skills courses that are available to anyone in Africa for free.
IBM has launched similar initiatives in Africa. In 2015, IBM announced a plan to expand its Africa Technical Academy and Africa University Program and invest US$60 million by 2017 to bridge the skills gap for technical talent in Africa. The goal of the program is to provide IT professionals with advanced skills in analytics, cloud, and Big Data technologies.
The training and certification programs are expected to benefit 1,000 faculty members and 35,000 students in eighty universities in more than twenty African countries by 2017.
In Kenya, for instance, IBM has partnered with the Kenya Education Network (KENET) in order to deliver advanced hands-on certification courses to faculty members and students in fifty universities.
IBM also has similar initiatives in other countries. For instance, universities in China, Qatar, Turkey, and other developing countries have participated in the IBM Cloud Academy, which allows access to a range of educational resources.
Education and R&D
Hewlett-Packard Laboratories in India has developed a cloud-based personalized education delivery system. It provides an online school hosting service, where a virtual school can be created using the infrastructure (servers, storage, communication, and e-learning software). Its facilities include audio/video sessions or online chats.
Vietnam started collaborations with IBM in 2007. In 2008, the US-based IT services company Computer Sciences Corporation (CSC) and Vietnam’s First Consulting Group Vietnam (FCG) merged. CSC developed its Vietnamese operation as a center for cloud operational and support services.
The University of Information Technology, a member of Vietnam National University, is using IBM PureFlex System, IBM Tivoli Service Delivery Manager, and IBM Workload Deployer to build a Smarter Computing IT infrastructure that hosts the university’s virtual campus and deploys virtual education services.
The cloud is used to link government agencies, universities, private- sector research, start-ups, and other organizations.
As a final example, the Netherlands- based technology company Philips has teamed up with the Chinese Society of Cardiology to build the China National Cardiovascular Data Repository. Philips is also reported to be working on other databases in China.
International organizations are also a driving force behind the adoption of Big Data and the cloud in e-learning and R&D. The United Nations Educational, Scientific, and Cultural Organization (UNESCO) and HP’s “brain gain” initiatives entail cloud use to connect students with researchers abroad.
The Burkina Faso’s University of Ouagadougou has launched projects modeling the movement of pollutants in the Sourou River drainage basin. By 2009, successful pilot projects were carried out in Ghana, Nigeria, Senegal, and Zimbabwe. By 2011, twenty educational institutions in sixteen countries benefited from the project.
Capacity Kenya, a USAID funded project, in collaboration with the Kenya Medical Training College and Africa Medical and Research Foundation, has hosted a local cloud environment that is used to locate and map healthcare specialists and develop virtual learning platforms for medical students.
International collaborations and development of research capacity are some of the initiatives underway in developing countries to overcome resource challenges. For instance, CLR’s EKA supercomputer, which was the world’s fourth fastest in March 2009, was used for joint cloud research with Yahoo.
Discussion and Concluding Comments
Big Data and the cloud are likely to address some of the challenges related to education and R&D in developing countries. A number of encouraging signs have emerged to suggest that Big Data and the cloud can transform the R&D and educational systems in developing countries.
E-learning tools such as Kio Kit epitomize the evolving role that Big Data and the cloud can play in enhancing educational outcomes.
The above discussion suggests that uses of Big Data and cloud in education are driven by philanthropic and charitable causes as well as motivated by profit-oriented behaviors. Various platforms used have different levels of sophistication of technologies.
Some platforms have been developed specifically for the developing world while others have been exported to developing countries following successful implementation in industrialized countries.
The above said, Big Data- and cloud-based learning solutions currently have a number of drawbacks and limitations. It is argued that teachers are “barely trained, unqualified, poorly paid.”
Students do not have access to their own tablets. Teachers are expected to all read the scripts aloud word-for-word and the contents are delivered on the tablet at the same time in each school every day. This “teacher turned- robot” would not be tolerated in most schools in most developed countries.
Kio Kit and Eneza are based on less sophisticated technological solutions, which are well-suited in the context of LDCs. In a developing country, a company's success depends on its ability to reduce costs.
For instance, Eneza is exploring a number of revenue streams in order to reduce the costs of student access. In addition, the systems need to consider the unique situations facing developing countries. For instance, the Kio Kit is a drop, dust, and water resistant.
A less discussed benefit is that the availability of a complete digital record of students’ achievement and performance significantly reduces the time to hire and recruit for potential employers.
For instance, Flipkart’s hiring decisions were based solely on the candidates’ Nanodegree projects and Udacity profile.87 In this way, Flipkart has eliminated the in-person interview for well-qualified students in Udacity’s Nanodegree program.
Prior theory and empirical research on the diffusion and adoption of e-commerce argue that firms based in developing economies face more barriers and obstacles to e-commerce utilization than those in industrialized countries.
Big Data and the cloud have been touted as a key mechanism for leveling the playing field for firms in developing economies, especially SMEs.
A key benefit of the cloud is that it helps to cut IT costs. The cloud also allows firms to benefit from a number of technologies without requiring a deep knowledge and expertise about the technologies’ underlying principles and concepts.
This means that firms can focus on their core businesses instead of being impeded by technical difficulties and obstacles.
Such benefits are of special value to firms in developing economies due to a number of economic, technological, and cognitive barriers they face in acquiring and using e-commerce technologies.
Most SMEs are not in a position to buy servers and storage and hire the IT staff to support them.
The key activities associated with e-commerce such as designing websites, using search engine optimization techniques, managing email marketing campaigns, and inventory management and hiring data engineers to capture complex data requirements are prohibitively expensive to build in-house for SMEs, and even for large enterprises in developing economies.
Thanks to the cloud, firms in developing economies are in a position to provide more sophisticated e-commerce-related functionalities and capabilities, complex features, and user interfaces. For instance, multi-channel e-commerce platforms provided by CSPs such as ChannelAdvisor help to synchronize a retailer’s e-commerce channels and its marketing strategy.
It also helps the retailer to expand to additional channels and take the e-commerce channel to the next level. Likewise, the Chinese company Alibaba’s AliCloud provides e-retailers with analytical data about website activities and predictions for indicators such as future sales and the products that are likely to be in high demand in the next period.
Unsurprisingly Big Data- and cloud-based e-commerce activities are diffusing rapidly in developing economies, and serving a wide range of users and geographic areas thereby contributing to bottom lines of e-commerce firms.
Consider China, the world’s largest online retail market, in which e-commerce accounted for more than 13 percent of total retail sales of consumer goods in 2016.
A McKinsey Quarterly article asserted that e-commerce penetration in top-tier cities is reported to be about 90 percent of Internet users.
Unsurprisingly, there has been a rapid growth of data related to a number of indicators such as online shoppers, stock keeping unit (SKU) of products, response to price changes, promotional performance, and purchase habits of online shoppers. China’s major e-commerce players are using this data to build models in order to increase customer spending and retention.
For example, Big Data can help segment and identify customer groups at different life stages and target offerings in order to increase sales. Some e- retailers are also reported to be using machine learning to make decisions related to product lines and promotional activities.
In some developing economies, Big Data- and cloud-based e-commerce activities are expanding from Tier 1 cities to smaller cities and villages. For instance, the Indian e-retailer http://Jabong.com, which uses cloud offerings from Oracle, Adobe, and other CSPs, receives 60 percent of its revenues from smaller towns.
In 2012, Alibaba announced that its cloud-based app, Alipay, had established a rural business unit to reach non- e-commerce users in third- and fourth-tier cities and in rural areas.
The evolution of cloud-based e-commerce has been a key driving force behind the rapid growth of the cloud industry and market in some developing economies. For instance, in Brazil, e-commerce firms, especially those exhibiting big seasonal variations in demands, have been among the early adopters of the cloud.
In India, companies such as http://MakeMyTrip.com and blogMyShow are using Big Data and the cloud to provide e-commerce offerings to benefit from the country’s rapidly expanding e-commerce market.
For instance, Flipkart is reported to analyze twenty- five million rows of inventory data every day in order to make data-driven decisions. Big Data tools are reported to help e-commerce companies such as Snapdeal and HomeShop18 to generate 30–40 percent of their orders.
The rapid diffusion of cloud-based e-commerce activities in developing economies is also associated with and facilitated by global CSPs’ entry into these economies. Firms in these economies are using e-commerce apps developed by global CSPs such as Google, Microsoft, Amazon, and Dell.
For instance, the Indian online store Flipkart’s cloud infrastructure is built on Dell PowerEdge servers. Another Indian retailer, Zovi, uses cloud apps of Google, AWS, and GitHub. Likewise, as of September 2014, over 2,000 Chinese e-commerce companies.
Regarding established foreign CSPs’ entry in developing economies, it is worth noting that they offer more sophisticated applications and services compared to local CSPs. In order to illustrate this, let’s compare AWS and Alibaba’s cloud offerings.
According to Alibaba’s filing with the US SEC for an IPO, its cloud was capable of handling 3.6 million transactions per minute in 2014. On the other hand, Amazon’s data storage system reportedly handled 1.5 million requests per second in 2013.
Likewise, as of August 2014, whereas Alibaba had only three Big Data centers in China and a smaller one in Hong Kong, AWS had twenty-five big and fifty-two smaller data centers worldwide.18 Local CSPs such as Alibaba, on the other hand, are more effective in providing cloud-based solutions suitable for local needs.
This blog assesses the roles of Big Data and the cloud in stimulating the e-commerce markets in developing economies and their potential in overcoming various e-commerce barriers in developing economies.
Specifically, we focus on Big Data and the cloud’s roles in overcoming economic, socio-political, and cognitive barriers, which are identified as key hurdles in firms’ and consumers’ e-commerce adoption in developing economies.
Following the OECD, we define an e-commerce transaction as the sale or purchase of products over the Internet or broad computer-mediated networks.
Some Examples of Big Data- and Cloud-Based E-Commerce Applications Deployed in Developing Economies
Key features of the cloud have made it an attractive choice for offering e-commerce solutions by domestic and foreign companies to serve the developing economies.
Zovi, a Bangalore India- based e-retailer, uses Google’s cloud application for communication and document storage and AWS for the application (e.g., relationship-marketing software, chat, email, browsing, e-banking, security applications) and analytics (e.g., tools that allow the company to personalize services and product recommendations).
For codes that drive the platform/ storefront, it uses the free open source hosting platform GitHub.
The company's Chief Technology Officer (CTO) noted that it made more sense financially and operationally to invest resources on the core business of software development rather than on hardware infrastructure and required maintenance.
He further noted that AWS deployment helped the company avoid spending US$1 million in initial capital expenses for hardware.
Foreign multinationals operating in developing economies have also used the cloud to offer their products online. In 2012, the French cosmetics company Clarins launched an e-commerce site in Demandware. Before that, the company had sold its products through other outlets.
According to Laurent Malaveille, executive vice-president for global digital, CRM and e-commerce, a cloud-based e-commerce platform can effectively outsource the system’s day-to-day technical operations.
The company’s e-commerce group got more time to focus on key features such as the loyalty program that is linked to the company’s success in online sales. The company reported a double-digit sales growth on its Chinese site in the first six months after the launch.
The Supply Side: Providers of Big Data- and Cloud-Based E-Commerce Solutions and Infrastructures in Developing Economies
As mentioned earlier, global CSPs’ entry has been a key factor in stimulating cloud-based e-commerce in developing economies. Microsoft’s Azure platform
During peak business days, our site may be hard to access for online shoppers. Without the cloud service, we would have to spend lots of money and time to install new servers, and many of them would be idle for normal days when we don’t have sales. Azure helps us save the cost of buying servers, and expands our site access capability only when we need it.
As a further example, Brazil’s e-commerce website platform Shop Delivery, which allows businesses to create and run their own online store, uses Microsoft's Azure.
Canada’s Shopify offers cloud-based POS software for brick-and-mortar retailers (e.g., a cash register to input products, tally costs, and conduct financial transactions, communicate with inventory levels, etc.) as well as to e-retailers.
For e-retailers, it offers site templates that can be customized, integrated shopping carts, search engine optimization (SEO) feature, email marketing, inventory management, and analytics.
Users also gain from the m-Commerce shopping cart, payment gateways to authorize credit card payments and social media integration. In July 2013, Shopify teamed up with Singapore’s SingTel to offer e-commerce solutions in Asia.
Shopify started offering localized e-commerce solutions in India, Indonesia, and Malaysia. About 1,000 new stores were created in the last week of August 2013 on Shopify in India.
GS-based technology companies are evolving rapidly and are playing key roles in the development of Big Data- and cloud-based e-commerce. Alibaba, which is now the world’s largest e-commerce company, is among the most high profile companies in developing economies with significant operations in cloud-based e-commerce activities.
It has been taking a number of initiatives to become a one-stop shop for SMEs conducting business online.
It provides services such as online marketplaces, back-end e-commerce merchant services, and its own cloud-computing e-commerce platform.30 As of September 2014, its e-commerce platform offered traditional features such as online storefronts and an order management system.
The company is planning to augment the depth of its offerings by expanding features to support online merchants. In August 2014, AliCloud introduced a data mining and analytics product known as Open Data Processing Service (ODPS), which provides e-retailers with analytical data about website activities.
The users of the service are required to pay about US$100 per month. When merchants enter sales data, the ODPS algorithm scans them and provides predictions for indicators such as future sales and the products that are likely to be in high demand in the next period.
Alibaba’s cloud computing business unit has also launched Aliyun Search, which will help users to research various brands and products in order to make buying decisions. Alibaba’s cloud unit also specializes in data management which involves e-commerce data mining and processing to customization.
Suggestions from Aliyun Search are reportedly based on buying behavior and the results are presented based on an e-commerce point of view.
Experts say that Alibaba is in the best competitive position to develop an e-commerce-oriented search engine since it can combine Yahoo’s search algorithm with purchasing insights from Taobao and ETao.
Note that Alibaba’s Taobao is China’s largest e-commerce platform and ETao is a comparison shopping engine, which reportedly had over a billion product listings and more than 5,000 B2C and group buying websites.
The cloud-based app, Alipay Wallet, allows users to link Alipay accounts to local bank accounts. Users can also transfer money into it from a prepaid account. In this way, it facilitates online payment services in e-commerce.
In August 2014, Alipay Wallet announced that it had released more than sixty new APIs for third-party developers in order to build online storefronts.
This means that online storefronts can integrate Alipay’s under-lying programming functions into their applications, which is expected to make it easier and faster for the merchants to develop Alipay Wallet virtual storefronts.
Alipay started recruiting merchants for its wallet app in June 2014. In two months, it recruited over 1,000 merchants.38 Retailers who set up in-app store-fronts can sell and market products to Alipay Wallet users and gain access to data analytic tools that allow them to personalize product recommendations.
Another visible Chinese e-commerce company is JD.com, Inc. It uses Big Data to keep inventories low and speeds up delivery.
It also employs sophisticated Big Data-based models to run financing for customers. JD.com, Inc. has formed a partnership with Tencent to integrate e-commerce into the WeChat app.
Based on what a user is buying and searching at JD.com, Inc., Tencent can send coupons in real-time. JD.com, Inc. has also made heavy investments in the IoT.
Its 3 System Fridge has sensors on every shelf and an internal camera. It registers the time and date when food items are stored inside.
The data is fed to a smart screen on the fridge’s front side, which alerts when an expiry date is coming close. It can also order the next grocery list from JD.com, Inc. based on the fridge’s contents.
As of mid-2016, JD.com, Inc. was working with the Joy Link platform, which connects a 3 System Fridge with the consumer’s digital devices. The internal camera can be accessed from a smart device’s app.
A consumer thus can check the fridge’s contents even when they are away from home and order groceries. The smart screen on the front also provides opportunities for advertising for e-marketers.
The Delhi-based customer segmentation and marketing automation platform Betaout offers a SaaS-based offering for e-commerce companies. It provides real-time data and machine learning to segment customers, which can help e-commerce companies retain customers, increase conversions, and personalize user engagement.
Another example of an e-commerce solution developed in developing economies is uafrica.com. It provides a platform to build a cloud-based e-commerce site (http://uShop.co.za). Its initial offerings included basic online store-front services.
The company plans to expand to additional services related to payments, logistics, and marketing supports and then to a multi-channel selling solution.
An important feature of uafrica.com/ basic product offering is the ability to trade via mobile devices.
As another example, in 2014, Nigeria’s Delivery Science launched a SaaS-based model which provides automated proof-of-delivery, intelligent transportation management, and inventory management to facilitate firms’ e-commerce activities. Delivery science’s Big Data applications help e-commerce and logistics businesses track and manage deliveries.
Its proof-of-deliver product has been updated to integrate services such as simple transport management, point-of-sale, and inventory management and allocation of products.
India’s Wipro offers cloud-based e-commerce solutions, including omnichannel B2B & B2C e-commerce, platform transformations, and marketplace implementation. Note that an omnichannel strategy involves supporting all channels with a holistic view of customer experience.
Omni-channel inter-actions are integrated and connected, and aim to provide rich customer experiences across devices, channels, time, and context.
DISCUSSION, IMPLICATIONS, AND CONCLUSION
The analysis provided in the earlier blogs of this blog suggests that Big data and the cloud have a disruptive and transformative potential for developing countries. It has pointed to a large number of applications that in different ways can support the implementation of many Sustainable Development Goals.
At the same time, benefits cannot be taken for granted and various risks will also emerge as more and more economic activities shift online.
For developing countries to seize the full benefits from Big data and the cloud, they, therefore, need to address a range of policy challenges, and effective support will be required from the international community.
The development and deployment of Big data and cloud computing solutions across key industries and economies in the global South show strikingly diverse patterns. Some organizations such as China’s Alibaba have developed and deployed sophisticated and well-engineered Big data and cloud systems.
However, the majority of the uses in the developing world need low- cost solutions that fit their specific needs as well as economic and infrastructural contexts.
The uses of Big data and the cloud in most developing countries have so far focused on only a few economic sectors. Put differently, the adoption of Big data and cloud tools in these economies is far from widespread and from being effectively integrated into the broader economic sectors.
For instance, in China, the three Internet giants Alibaba, Baidu, and Tencent are believed to have the same level of caliber and skills in Big data as Western technology companies.
However, many of China’s other industries are lagging behind. Observers have noted that telecommunications, banks, governments, and medical institutions are far from harnessing the full power of Big data.
The integration of Big data, the cloud, and mobile computing technologies offer particular promise for facilitating economic productivity and social development in developing economies.
The Mifapro and other cases highlighted in this blog show that they can play a key role in promoting the well-being of disadvantaged groups, improve the functioning of markets for agricultural produce, and affect the allocation of resources.
Enhanced availability of information can also help to better evaluate the risks and uncertainties for various market participants.
Big data and the Cloud in Developing Countries in Relation to Innovation and Technological Progress
Many business and government policy initiatives directed toward improving innovation performance in Big data and the cloud areas have been launched by the private sector and national governments in developing economies.
As a result, some emerging economies are already evolving as hotbeds of innovation in these areas, perhaps most notably in China.
But excellence is also visible elsewhere. Some SSA-based firms are impressive in their ability to bring together innovations involving local capacity building. In a 2011 survey of the world’s top experts on Internet-related innovations, 7 percent viewed Africa as “the most innovative place for Internet-related technology.”
The corresponding proportions for other regions and economies were: Europe: 4 percent; China: 4 percent; India: 7 percent; and the Pacific Rim: 5 percent.
The experts viewed Africa’s Internet-related innovations as: “On-the-ground solutions designed by communities for communities.”2 India’s relatively poor R&D and innovation performance has led some experts to argue that entrepreneurial activities in the Indian ICT and offshoring industry have a “hollow ring.”
An Economist article notes: “India makes drugs, but copies almost all of the compounds; it writes software, but rarely owns the result . . . [it has] flourished, but mostly on the back of other countries’ technology.”
In view of the prominent roles of some Indian technology firms in the global arena, they have shown less impressive performance in generating innovative solutions to solve local problems.
This points to a general observation made by the United Nations, that developing countries should give due attention to leverage their indigenous ICT and especially software industries to serve local development needs and demands.
Foreign multinationals are also helping to stimulate and facilitate innovation in developing countries. For example, IBM built its forty-first global Innovation Center in Kenya’s Nairobi in 2013, which is first such Center in East Africa.
A key focus of the Center is on mobile and cloud technologies to solve local and global challenges, such as traffic congestion and better energy management.
As of early 2016, IBM Research Africa had about thirty-five specialists in Kenya in diverse fields such as computer sciences, engineering, and environmental science. In addition, the Nairobi lab had thirty- five software developers and trainees from local universities.
Innovations in privacy and security are focusing on smartphones and wearable devices. For instance, HID Global, which manufactures access control cards that are used to open doors in offices and hotel rooms, has teamed up with chipmaker NXP Semiconductors to expand the technology to work with smartphones and wearables (e.g., Apple Watches and Android Wear).
Due to privacy concerns, HID’s platform will allow individuals to decide the amount of information shared.
For example, a police officer can be given access to more detailed data than a liquor store worker that merely wants to verify a customer’s age. The owner sends it from his/her smartphone.
The company is pushing several Big data projects including digitization of Nigeria’s entire vehicle ownership system. The goal is to put the country’s more than fifty million cars onto a database that is accessible by a smartphone.
Big data- and cloud-based tools such as Sproxil’s MPA system can realize economies of scope by providing services in other sectors.
For instance, manufacturers have started using Sproxil’s MPA system to eliminate counterfeit products. A survey conducted by Schneider Electric showed that counterfeit electrical products account for 40–80 percent of their markets in African countries.
Some of the most counterfeited electrical products include sockets, cables, switches, and extension cords. In 2012, Nigeria’s hair- and skin-care product manufacturers and the Swiss company O’tentika started a collaboration with Sproxil, and East African Cables also employs Sproxil’s systems to fight counterfeits.
Challenges and Obstacles Associated with Big data and the Cloud
There are a number of challenges to overcome in the deployment of Big data and the cloud in the developing world.
Changing Skills Requirement
A major concern for harnessing the full potential of Big data and the cloud is the lack of relevant skills, knowledge, expertise, and experience.
In a survey conducted by the online recruitment website Monster Jobs - Job Search, Career Advice & Hiring Resources, 68 percent of employers in the Middle East and India believed that it was “extremely difficult” or “difficult” to hire talent for technology.
In another survey by Accenture among Indian enterprises, 53 percent of the respondents cited the lack of talent to be a key challenge in Big data and cloud deployment.
McKinsey estimates that India will need 200,000 data scientists in the near future. Snapdeal.com said that the company has not been able to find the coders and other Big data manpower it needs.
The company recognizes the need for world-wide recruitment for experienced programmers dealing with Big data, cloud computing, and the software for interacting with customers and suppliers.
Snapdeal was hiring cloud specialists from the United States as well as considering establishing a software development center in the USA, and buying firms there in order to capture the needed manpower.
According to the Internet & Mobile Association of India, there were 50,000–70,000 mobile developers in India in 2015. It is estimated that twenty million developers will be needed by 2020.
Skill deficits for Big data and the cloud often reflect broader problems of low educational quality, achievement, and standards. For instance, the inability of Vietnamese universities to train the next generation of highly- skilled workers has been a significant roadblock in this context.
Likewise, according to the UNESCO, only 6 percent of Africa’s young people are enrolled in higher educational institutions compared to the global average of 26 percent.
A large number of organizations in Africa have had limited experience in data cleansing or standardization. There is thus a general lack of skills in the advanced techniques and technologies required for Big data. South Arica is estimated to require at least 200 data scientists to participate in the SKA alone.
High Data Creation and Data Access Costs
High costs are a major obstacle for consumers to engage in activities that generate data. Consider South Africa. Consumers with an income of R3,000 (US$225) a month, which is significantly above the national minimum wage, needed to work around eighteen hours in order to afford a 500 MB data plan.
Thus, even if consumers can afford smartphones, they often cannot afford to use them other than like “dumb” phones.19 At the 2016 price level, only a quarter of Indonesians and 22 percent of Chinese could afford data consumption of 500 MB per month.20 From a pure cost perspective, in order to get everyone online, data prices need to fall by 90 percent or more.
As of 2016, developing economies had only seventy-seven Internet exchange points compared to 134 in the developed economies. North America with a population of 350 million had eighty-five IXPs compared to eight in South Asia with a population of 1,760 million.
Resistance from Vested Interests
Resistance from some powerful actors, who derive their market position and authority by controlling or selectively sharing access to information, can be a huge obstacle. Increasing access to data and information can threaten such actors’ current sense of power and authority.
Consider the lack of disclosure of data related to soil pollution in China. Between 2006 and 2010, China’s Ministry of Environmental Protection (MEP) and the Ministry of Land and Resources
Discussion, Implications, and Conclusion
(MLR) conducted surveys of soil pollution in China. A 2014 report indicated that 16 percent of about 10,000 testing points failed to meet the specified standards. Analysts argued that there are significantly more polluted sites than the testing points covered by the surveys.
One estimate suggested that China has between 300,000 and 500,000 polluted sites, or thirty to fifty times higher than the number of testing points covered in the surveys.
Implications for Technology Marketers
There are a number of implications for technology marketers and technology entrepreneurs.
Involving Relevant Stakeholders
It is important to identify broader relevant stakeholders, especially users, and increase their involvement in the design process. For instance, the experiences of mobile cloud-based e-learning in SSA economies indicate that teachers can play a crucial role in designing, developing, and implementing education-related technologies.
Likewise, in the development of healthcare applications, collaboration with end-users such as health facility staff, community health workers, or community leaders is essential to inform program design and improve implementation in the local context.
Considering Technologically Unsavvy and Less Savvy Users
In formulating policies and designing Big data- and cloud-based mobile computing solutions tailored to the needs of developing countries, it is helpful to consider the extent to which end- users are technologically savvy or less savvy. The cloud-based systems used in developing countries need to be technically as simple as possible.
In the MADEX system, for instance, pressing the send button is the only action that is required to be taken by midwives in order to send monthly reports. Likewise, an entrepreneur making a sale using Lula is required to press only a few buttons.
Involvement and Mobilization of Local Talent and Resources
The successful initiatives in Big data- and cloud-based mobile computing solutions in developing countries are mainly indigenously triggered, albeit often with the involvement of foreign companies. They are also oriented towards the active involvement of local communities and the mobilization of local entrepreneurial resources.
For instance, Nomanini’s success can be largely attributed to the founders’ expertise in ICTs and an in-depth and intimate understanding of the African market. The founders noted that Lula is a uniquely “South African born-and-bred solution” that targets the needs and interests of the local population.
It was a team of programmers in Kenya who developed the EpiSurveyor system. The Farmforce platform was developed in 2011 by a team based in Switzerland with inputs from a team based in Kenya. Likewise, Kenya- based Safaricom in partnership with the local organization Green Dreams envisioned and developed the iCow system.
In 2011, Safaricom launched Safaricom Cloud, arguably Africa’s “largest native cloud deployment.”
It started hosting Mpesa mobile money services locally and launched new cloud offerings, including hosting platforms for government agencies and corporations. As of 2011, the company had invested US$150 million in clouds and announced plans to invest additional US$200 million.
Safaricom teamed up with Cisco for storage facilities, EMC for security, and Seven Seas Technology for training managers.
Consideration of Affordability, Open Source, and Other Related Aspects
For global IT providers, affordability and customization to meet the local requirements will be a key consideration to compete in developing countries.
Regarding the benefits of Android phones over low-cost feature phones, the director of ICT innovation at the Grameen Foundation noted that the open source nature of Android allowed Grameen to hire its own developers to customize the phones.
The customization enabled an improved use of power and to make applications usable when the phones are not connected to a network.
A related point is that Big data- and cloud-related products and services offered in developing markets must recognize—at least in the short run—the local technological reality, such as low bandwidth and mobile-driven digitization.
Finally, the diffusion of Big data- and cloud-based mobile computing solutions is an issue that has policy implications for enhancing agricultural productivity and food security, creating rural employment and reducing poverty.
Big data- and Cloud-Related Innovations from the South for the South
Some innovations in Big data- and cloud-based mobile computing are from the South (developing countries) for the South, an encouraging trend in the new geography of global innovations.
As discussed earlier, a number of developing world-based technology companies such as Alibaba, Tencent, Green Dreams, and DataDyne have developed unique Big data- and cloud-based apps for the developing world.
In September 2011, Novatium services had over 40,000 users in India. Ericsson’s principal target groups for the applications are emerging markets, where most consumers cannot afford a PC. In developed markets, the company focuses mainly on young consumers.
As mentioned, Big data- and cloud-based mobile computing solutions hold a special appeal for developing countries. Such solutions provide the best opportunity to overcome barriers related to ICT infrastructures and level the playing field for MSMEs.
A number of philanthropic foundations’ support to these technologies have facilitated the diffusion of Big data- and cloud-based mobile computing solutions in developing economies.
Governments have a critical role to play in order to overcome barriers related to skills shortages, information gaps, poorly functioning markets, and inadequate infrastructures by adopting and implementing relevant policies, laws, and regulations. Such mechanisms are also needed to accelerate the development of the Big data and cloud industry and market.
Investor-friendly policies such as tax incentives, subsidized credits, infrastructure investment, market deregulation, and special startup programs can help attract Big data and cloud companies.
The Internet & Mobile Association of India (IAMAI) called for new tax incentives for locating data centers in a country: direct corporate tax rates and indirect sales taxes.
China’s Guizhou province (blog 1) also illustrates this point. Favorable policies are elevating Guizhou from being one of the most backward provinces to a prominent Big data hub. The province’s per capita GDP in 2015 was less than two-thirds of the national average. Guizhou offers various tax breaks and grants to technology firms.
Big data enterprises that meet certain requirements are exempt from corporate income tax for the first two years and benefit from a 50 percent corporate income tax reduction for the following three years.
The province also offers housing allowances to attract Big data talent. Companies can register in the Guizhou province, without setting up physical facilities.
In 2014, the governments of Guizhou province, Guiyang City, and Gui’an New District agreed to work together to allocate at least 100 million CNY annually during 2014–2016 to develop the Big data industry. In 2016, the Guizhou province announced plans to invest a further 100 billion yuan to develop the Big data and cloud sectors.
What is viewed as a disadvantage for an economy can actually be an advantage in the Big data era? For instance, the Taiwanese manufacturer Foxconn took advantage of Guizhou’s cool weather to establish an air- conditioning-free data center inside a cave located on a mountain in the province.
In light of rapid technological change, developing countries need to manage privacy and security matters in Big data and the cloud by issuing forward-looking regulations that manage risks associated with the evolution of new technologies.
For instance, an estimate by Gartner suggested that IoT security will account for 20 percent of annual security budgets by 2020 compared to less than 1 percent in 2015.
As was highlighted above, many governments in developing countries need to strengthen their legal and regulatory framework in the field of data protection and privacy.
Chinese companies such as Huawei, Alibaba Group, and ZTE have emerged as challengers to global cloud providers such as IBM, Amazon, and HP, initially in their domestic market but also internationally.
This phenomenon fits well with the theory of kaleidoscopic comparative advantage, which argues that “the nature of comparative advantage is becoming thin, volatile, and kaleidoscopic and is creating vulnerabilities for industries, firms, and workers.”
In the least developed economies, the potential opportunities and benefits have been limited by weak forward and backward linkages. Unsurprisingly, global IT companies have been slow to enter into these economies.
When they enter and intensify their activities, however, mechanisms such as labor mobility and stimulation of knowledge and technology transfer and other spillover effects may help local firms develop their capabilities—if they have a certain basic level of absorptive capacity.
Some applications of Big data and the cloud can help create a virtuous circle, which can act to positively reinforce the further development of the cloud industry. In Vietnam, cloud computing is being used to develop education programs, which would help further strengthen backward linkages.
Nonetheless, the overriding reality is that in developing economies, only a small proportion of organizations and firms are currently positioned to take advantage of advanced technologies such as Big data and the cloud.
IT-intensive industries (e.g., software development in China) or those dealing with IT-enabled processes (e.g., offshoring sectors in South Africa) are benefiting more from Big data and the cloud than most other economic sectors.
With improved connectivity and awareness, however, Big data and the cloud are likely to gain momentum in the developing world.
Big data- and cloud-based business models are still evolving. For local and global cloud providers, success in developing economies hinges on having business models that focus on affordability and consider the unique needs and capabilities of small-scale consumers (including MSMEs).
Governments in the developing world can collaborate with domestic and foreign cloud players to support the development of software and other products appropriate for local needs.
Cloud-related innovations and business models that leverage existing infrastructure and technologies in novel ways undoubtedly have potential benefits. Perhaps the greatest barrier for the adoption and effective utilization of the cloud in the developing world is the low PC penetration and a limited as well as expensive bandwidth.
This will favor the mobile-based cloud solutions in low-income countries. First, a cell phone capable of running a browser can already access mobile clouds.
Low-cost phone users can thus tap into applications that are currently accessible only through smartphones. Second, consumers in the developing world are using increasingly sophisticated devices.
Not long ago, there were very few applications available for developing world-based users such as China Mobile’s BigCloud platform and Salesforce’s “offline PDA.”45 Now, cloud-based mobile applications are becoming increasingly pervasive, which are set to transform the way mobile phones are used in the developing world.
Lessons and Implications
Big data and the cloud in most developing countries are still at an early stage of development.
Rather than viewing these technologies as a self- contained phenomenon, they must be seen against the backdrop of economic and institutional realities.
In theory, there are many possible uses of Big data and the cloud and several channels and mechanisms through which developing economies may benefit.
In practice, however, serious problems stand in the way of implementation and practical gains. Big data- and cloud-based innovations and business models are yet far from inclusive of SMEs in the global South, especially in the least developed, small nations.
Currently, Big data and cloud usage have been shallow, narrow, and vanishingly small in most developing economies. Small developing economies lack the infrastructure and economies of scale for wide and deep cloud adoption. It would thus be unreasonable to expect that the cloud would help the developing world catch up with the West in one big leap.
However, as economic and institutional factors improve, Big data and the cloud offer a possible avenue towards bridging the digital divide. The developing world thus should seek to exploit the opportunities afforded by the cloud while minimizing the associated risks to allow access to advanced IT infrastructure, data centers, and applications, and protect sensitive information.
Some potential impacts of the cloud in the developing world include productivity gains, the development of innovative services (e.g., personalized insurance), efficient supply chain management, implementation of B2B e-commerce, and the development of a skilled workforce. We argued that the cloud might erode the comparative advantage of incumbents.
While some developing world-based companies such as Alibaba and Zoho have challenged industrialized world-based multinational companies, in the present context, cases like those are extreme.
Future Research Implications
Before concluding, we suggest several potentially fruitful avenues for future research. First, in terms of geographic focus, we limited our analysis to a few major economies. For instance, some of the most high-profile and interesting Big data projects in the primary sector are being undertaken in Vietnam.
In the future, conceptual and empirical work scholars need to compare and contrast the cloud and Big data development processes in developing economies not considered in this blog.
In this blog, we reviewed several Big data- and cloud-based solutions that have been developed locally as well as in the developed world.
The second area of future research might be to compare locally developed Big data and cloud solutions with those developed in the industrialized world in terms of a number of parameters such as costs and performance.
Such research should also consider how technology transfer within developing economies might compare with North-South transfers.