Abstract
In the digital space, Robotic Process Automation (RPA) is drawing more attention in the corporate world. The advent of RPA has the potential to disrupt the traditional Humanitarian Disaster Response Value Chain (HDRVC). The gaps unmasked by the analysis of the HDRVC make coordinating the organizational activities and finding the right resources to combat the catastrophes difficult as it requires time and money, which neither the humanitarian agencies nor the victims have during a disaster. The objective of this project was to analyze the HDRVC and establish opportunities within which RPA can be applied to bring efficiency and effectiveness in the value chain system. The project used Porter’s Value Chain Framework to analyze the HDRVC and sought to validate the framework as suitable for HDRVC analysis. The project used a descriptive case study of World Food Programme to understand the opportunities in which RPA can be applied. Results showed gaps in the HDRVC which create the best opportunity to apply RPA in ensuring fast, efficient, and cost-effective aid delivery to the beneficiaries. Further results using the Confirmatory Factor Analysis (CFA) in Structural Equation Modeling (SEM) to test and validate Porter's value chain framework as suitable for HDRVC indicate that PVCM is reasonably near a perfect fit. Consequently, PVCF was found suitable for HDRVC. These results can be used by different other humanitarian organizations to tailor their value chain to assume seamless, effective, and efficient aid delivery. The results provide a concrete tool that can be used by different organizations, regardless of the industry, to analyses their value chain system in quest for effective service delivery. This research project envisages the future of the humanitarian sector by introducing RPA and describing its usage in revolutionizing the HDRVC by creating a seamless, effective, and efficient aid delivery system. Despite the overwhelmingly positive results, we acknowledge that qualitative study methods do not guarantee validity and reliability. As such, considerations for RPA-based aid delivery operations and a series of research questions are presented with the objective to create a dialogue in this evolutionary area. Ultimately, to remain relevant, organizations must combine innovative technologies with the skills and knowledge of qualified professionals.
Table of Contents
Declaration ii
Acknowledgement iii
Abstract i
Table of Contents ii
List of Tables iv
List of figures v
Abbreviations vi
Definition of Key Terms vii
CHAPTER 1: INTRODUCTION
1.1. Background 8
1.2. Problem Statement 9
1.3. Objectives 10
1.4. Research Questions 10
1.5. Significance of the Study 11
1.6. Assumptions 11
1.7. Limitations 12
CHAPTER 2: LITERATURE REVIEW
2.1. The World Food Programme (WFP) 13
2.2. Humanitarian Logistics 14
2.3. Humanitarian Disaster Response Value Chain 15
2.4. Robotic Process Automation (RPA) 16
2.5. Robotic Process Automation in HDRVC 19
2.6. Analysis of Legal, Ethical, Social and Political Issues in RPA 21
2.7. User-Robot Interaction in Disaster Response 22
2.8. RPA and Covid-19 Pandemic 23
2.9. Justification of RPA in HDR Value Chain 24
2.10. Existing Theoretical Frameworks 25
2.11. Research framework: Porter’s Value Chain Model (PGVCM) 27
CHAPTER 3: RESEARCH METHODOLOGY
3.1. Research Philosophy 29
3.2. Research Design 29
3.3. Source of Data 29
3.4. Data Collection 30
3.5. Data Analysis 30
3.6. Sampling Frame 30
3.7. Sampling Technique 30
3.8. Sample Size 31
3.9. Validity and Reliability 31
3.10. Ethical Issues and Consideration 31
CHAPTER 4: RESULTS AND DISCUSSION
4.1 Response Rate 33
4.2. Reliability Analysis 33
4.3. Demographic Data of the Respondents 33
4.4. World Food Programme Disaster Response Value Chain 35
4.5. Use of Robotic Process Automation (RPA) To Create Efficiency within the Humanitarian Value Chain 47
4.6. Potential of Implementing Robotics Process Automation in HDRVC 49
4.7. Validation of Porter's Value Chain Framework in HDRVC 51
4.8. Proposed Visual Representation of the Results and RPA Application 55
CHAPTER 5: SUMMARY, CONCLUSION AND RECOMMENDATIONS.
5.0. Summary of Findings 56
5.1. Conclusion 58
5.2. Recommendations 59
5.3. Further study 59
REFERENCES 60
APPENDICES 66
Appendix 1: Sample Quantitative Questionnaire 66
Appendix 2: Sample Qualitative Questionnaire 74
Appendix 3: Project Schedule 75
List of Tables
Table 4.1: Demographic Information 34
Table 4.2: WFP Primary Value Chain Activities 36
Table 4.3: Challenges in the primary activities of the value chain 36
Table 4.4: Time required to successfully respond to a disaster (In months) 37
Table 4.5: Possible causes of delays in the primary activities of the value chain 38
Table 4.6: Communication between various actors before and after a disaster 38
Table 4.7: Source/Organizations helping 39
Table 4.8: Methods of conducting beneficiary follow-ups after a disaster 39
Table 4.9: Secondary value chain activities of WFP 40
Table 4.10: Activities Supporting Primary Value Chain Activities of WFP 40
Table 4.11: Subcontracted Activities 41
Table 4.12 Reasons for subcontracting 41
Table4.13: Challenges in the secondary activities affecting aid delivery 42
Table 4.13: addressing challenges 42
Table 4.14: Use of Additional Financing 43
Table 4.15: Equipment/Machinery/Technology for improving aid delivery 43
Table4.16: Duration of contracts for new recruits 44
Table 4.17: number of the recruits hired at every onset of a disaster response 45
Table 4.18: Reasons for Recruitment at the Onset of a disaster 45
Table 4.19: World Food Program Value Chain Goal 45
Table 4.20: Problems with Reaching Value Chain Goal 46
Table 4.21: Causes of the problems with reaching the value chain goal 46
Table 4.22: Reasons for Increased beneficiary numbers 47
Table 4.23: Activities Carried Out by WFP to increase performance 47
Table 4.24: Goodness-of-fit Framework Results 52
Table 4.25: Convergent Validity Test 53
Table 4.26: Discriminant Validity Test 53
List of figures
Figure 2. 1 Stages of RPA implementation in an Organization 19
Figure 2. 2 Conceptual Research Model based on Porter’s Generic Value Chain Model 27
Figure 4.1: Delays in responding to disasters where n is the total number of respondents 37
Figure 4.2: Assistance on aid delivery to affected communities 39
Figure 4.3: Subcontracting of Secondary Activities Processes 41
Figure 4.4: Hiring of New Staff at the Onset of a Disaster 44
Figure 4.5. Proposed visual representation of the results and RPA integration 55
Abbreviations
BPMS - Business Process Management System CFA - Confirmatory Factor Analysis
HDRVC - Humanitarian Disaster Response Value Chain
HLP - High-Level Panel of the United Nations Secretary-General on Humanitarian Financing PVCM – Porter’s Value Chain Model
RPA – Robotic Process Automation SEM - Structural Equation Modeling IA – Artificial Intelligence
ML – Machine Learning
UNWFP – United Nations World Food Programme GOF- Goodness-of-fit
TLI – Tucker Lewis Index CFI – Comparative Fit Index
RMSEA – Root Mean Square Error Approximation GFI - good-of-fit index
Definition of Key Terms
Automation - This is a term used for technology applications in processes to minimize human involvement in their execution
Humanitarian Disaster Response - It is the process through which international humanitarian organizations such as the United Nations and other Non-Governmental Organizations deliver aid to the affected communities during a catastrophe.
Robot - It is a software embodied artificially intelligent agent that can perceive its surroundings, executing computations to make decisions, and acting in the real world in ways that humans would normally do.
Robotic Process Automation It is a software-based methodology for automating processes via the use of technology that is guided by business logic and structured inputs.
Robotics - An interdisciplinary subject that combines computer science and engineering, robotics is concerned with the design, building, operation, and usage of robots.
Value Chain - A value chain is a collection of actions carried out by a company to generate value for its consumers.
CHAPTER 1
INTRODUCTION
1.1. Background
Robotic Process Automation (RPA) is a technology that mimics human workers to complete specified jobs quickly and efficiently (Fung, 2014; Lacity et al., 2015). Business logic and structured inputs guide this software approach to automating activities (Lacity et al., 2015). RPA, powered by AI, has emerged as a prominent digitalization area. AI-driven robots and technologies will unlock human productivity in the next few years (Beerbaum, 2021; Körner, 2018; Heymann & Schattenberg, 2017; Kerremans, 2018).
As exemplified by the UN's 2030 Agenda, robotics, automation, and AI can solve many societal concerns. They can improve process performance, efficiency, scalability, accountability, security, and process compliance concequently increasing standard of living and improving the quality of life in developed and developing countries respectively (Madhavan, 2019). It is simple to implement and relatively inexpensive compared to traditional process automation, with the ability to execute tasks autonomously uninterruptedly, quickly, flawlessly, and traceably (Asatiani & Penttinen, 2016; Fung, 2014; Lacity et al., 2015; Lacity et al., 2017). The use of hardware robots has been extensively applied in humanitarian contexts for a substantial period (van Wynsberghe & Comes, 2019). However, despite the importance of software robots and RPA in humanitarian operations, their study and application have been overlooked.
A compelling HDRVC stream should drive the need to improve the population's quality of life affected by disasters. Madhavan et al. (2015) explain how researchers, practitioners, humanitarian relief workers, responders, field analysts, and humanitarian aid agencies can exploit Robotics and Automation to alleviate human suffering. Like any other organization, humanitarian organizations' value chain is embedded in a more significant stream that Porter calls the value system. Disasters call for the humanitarian value system's players to collaborate. Consequently, the humanitarian organizations' value system comprises the governments, the military, civic society, and humanitarian groups that find answers that can alleviate the pain of the affected communities in a disaster. The efficient and scalable execution of non-value(cost) activities and the reduction in turnaround times represent an excellent opportunity to use RPA in humanitarian disaster relief (Hofmann et al., 2020; Sutherland, 2013). Value creation in this regard would be through an efficient and compelling Humanitarian Disaster Response Value Chain (HDRVC) geared towards fast, timely, and cost-effective responses to disasters. After all, Porter insists on a firm's capacity to innovate and upgrade as essential factors leading to its ability to compete in the industry (Porter, 2008). It is crucial to emphasize the value chain in the humanitarian sector as it defines how much an organization can respond to an inevitable catastrophe.
Catastrophic uncertainty in terms of location, time, and severity brings a challenge in pre and post- disaster response due to the insufficient supporting processes and resources, including; financial, human, technical, and informational, all of which can delay the reaction time in humanitarian organizations (Modgil et al., 2020; Balcik et al., 2010). Additionally, the relief workforce frequently includes short-term volunteers or temporary workers, neither of whom may have the necessary experience to coordinate activities during a disaster relief effort (Modgil, Singh, and Foropon, 2020; Balcik et al., 2010; Pushpa Kumar & Asta Lakshmi, 2015). Planning and executing these activities and finding the right resources to combat the catastrophes requires time and money, which neither the humanitarian agencies nor the victims have during a disaster (HLP, 2016; Balcik et al., 2010; Modgil et al.,2020).
To create and sustain superior performance in service delivery during a crisis, humanitarian organizations must adopt an efficient and effective HDRVC. Analysing the value chain processes of the United Nations World Food Programme will provide insights into the gaps, challenges and an opportunity within which RPA can be utilized to improve humanitarian efforts’ efficiency (saving time) and productivity (saving costs) (Madhavan et al., 2015; Asatiani & Penttinen, 2016; Lacity et al., 2015). With RPA, humanitarian organizations will have an increased competitive advantage which will create a virtuous circle by attracting more funding and participants in humanitarian crisis response and, in turn, bridge the funding gap (HLP, 2016; Balcik et al., 2010). Furthermore, an efficient and effective value chain leads to fast aid delivery because employees will focus on the more value-adding activities involving personal interaction, problem-solving, and decision-making (Syed et al.,2020). Therefore, no one would have to die or live-in deplorable conditions due to a lack of funds or slow response by the aid providers. It would be a significant win for humanity at a crucial time.
1.2. Problem Statement
Uncertainty in terms of location, time, and severity complicates pre- and post-disaster response. The insufficient supporting activities and resources (financial, human, technological, and informational) affect the performance of the value chain system and worsen the situation leading to delayed aid delivery (Balcik et al., 2010; Modgil et al., 2020; Pushpa Kumar & Asta Lakshmi, 2015; Porter, 1985). Often, humanitarian organizations combat this by outsourcing some of the services at every disaster occurrence (Balcik et al., 2010; Modgil et al., 2020). As a result, there is a creation of rule-based, tedious, repetitive, and prolonged processes yet crucial in delivering aid to the beneficiaries. Consequently, coordinating these support activities and finding the right resources to combat the catastrophes requires time and money, which neither the humanitarian agencies nor the victims have during a disaster (Balcik et al., 2010; HLP, 2016).
Hardware robots have been used to automate primary value chain tasks in the humanitarian sector, whereas software robots have been used less for secondary operations. Porter (2008) emphasizes the necessity of simplifying secondary operations since delays or malfunctions in one value chain activity affect the cost or performance of others. Analyzing the HDRVC will expose gaps, opportunities and challenges within which RPA can be leveraged to ensure cost-effective and timely disaster response.
1.3. Objectives
1. To analyze the World Food Programme Disaster Response Value Chain
2. To evaluate how Robotics Process Automation can create efficiency within the Humanitarian Disaster Response Value Chain.
3. To evaluate the potential of implementing Robotics Process Automation in the Humanitarian Disaster Response Value Chain.
4. To validate the Porter's Value Chain framework as suitable for Humanitarian Disaster Response Value Chain.
1.4. Research Questions
1. What are humanitarian value chain's technical gaps?
2. What is the potential of implementing RPA in the HDRVC?
3. How can RPA create efficiency in the humanitarian value chain?
4. What are the effects of an effective and practical value chain in HDR?
5. What is the cause of an ineffective value chain in the HDR sector?
6. What are some of the existing value chain frameworks?
7. What are some of the existing framework validation methods?
1.5. Significance of the Study
The validated framework will provide guidance to humanitarian organizations, public sector organizations, and NGOs on technology adoption for an efficient and effective HDRVC. For humanitarian organizations and NGOs, the research enhanced the existing body of knowledge on software automation for disaster response. Significant effort has been dedicated to the automation of the primary value chain activities in the humanitarian sector using hardware robots, but less has been done in exploiting the software robots for the secondary activities of the HDRVC. Many researchers have emphasized the need to use automation in alleviating the suffering of the affected communities (Madhavan et al., 2015). RPA can tackle conventional and emerging humanitarian concerns.
This project, which provides an overview of the benefits of the integration of RPA into the humanitarian disaster response, will be a guiding reference to the organizations seeking to improve the quality of their HDRVC. The project will educate and convey to humanitarian organizations, non-governmental organizations, and wider public sector organizations how the use of RPA may enhance productivity, operations, and service delivery.
The project will bring together universities, technology companies, NGOs and other humanitarian organizations in conducting more research and realizing the right skills and capabilities in the industry. Effectively, there is an expected skyrocket of IT enabled professionals which will be a significant milestone towards the right skills in any field.
1.6. Assumptions
That the respondents shall agree to participate in the study with total honesty and without fear of any possible repercussions.
1.7. Limitations
Using qualitative study methods means validity and reliability of data collected is not guaranteed. Moreover, replicating a study with qualitative research is extremely difficult as it occurs in natural settings.
The Survey method used in data collection does not always guarantee the correct picture of events.
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