The Influence of Coordinating Logistics Services on Service
Performance in Slow and Sudden On-set Disaster Response
Master Thesis, SCM
Faculty of Economics and Business University of Groningen
Name: Amy English Student number: 2931273
E-mail:
a.m.english@student.rug.nl
Supervisor: N. Dube Co-assessor: J. van Leeuwen
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Acknowledgement
Firstly, I would like to express my gratitude to all of the professionals in the humanitarian and commercial sector that I interviewed. I thoroughly enjoyed getting practical insights from disaster response operations and these interviews allowed me to develop a better understanding of the topic. I would also like to thank my family for supporting me through my studies and Shaun for motivating me over the last two years.
3 TABLE OF CONTENTS ABSTRACT ... 4 1. INTRODUCTION ... 5 2. THEORETICAL BACKGROUND ... 8 2.1SERVICE PERFORMANCE ... 8
2.2SUDDEN AND SLOW ON-SET DISASTER RESPONSE... 8
2.3COORDINATION MECHANISMS IN A DISASTER RESPONSE ... 9
3. METHODOLOGY ... 12 3.1RESEARCH DESIGN ... 12 3.2RESEARCH CONTEXT ... 12 3.3DATA COLLECTION ... 13 3.4DATA ANALYSIS ... 14 4. RESULTS ... 17 4.1SUDDEN BUYER ... 17 4.2SLOW BUYER ... 19 4.3BUYER ALL ... 23 4.4PROVIDER ALL ... 25
4.5CROSS-CASE ANALYSIS ... 28
5. DISCUSSION ... 30
5.1SUMMARY OF FINDINGS ... 30
5.2IMPLICATIONS FOR RESEARCH ... 32
5.3IMPLICATIONS FOR PRACTICE ... 32
6. CONCLUSION ... 33
REFERENCES ... 34
APPENDICES ... 39
APPENDIX A-INTERVIEW PROTOCOL ... 39
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ABSTRACT
The purpose of this research is to identify the challenges faced in slow and sudden on-set disaster response operations in order to pinpoint opportunities for improving vertical coordination and in turn, service performance. The research is qualitative using a multiple case study approach. Primary data collection took place over Skype calls with professionals in the humanitarian and commercial sector internationally and data was analysed through a coding process using AtlasTi. Results indicate that sudden and slow on-set disaster response operations face many similar challenges. Coordination mechanisms used between international humanitarian organisations and logistics service providers generally allow for a faster response time and more flexibility, although there is much room for improvement in terms of allowing logistics service providers greater input into the decision making process. Time limitations meant dyadic relationships could not be explored; therefore the general perspectives of both organisation types are identified but their direct effect on each other cannot be determined. As disaster response operations have many reasons to improve their performance, this research provides insight into how LSPs and IHOs can improve their relationships through coordination.
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1. INTRODUCTION
Disasters are unplanned events with the potential for human suffering as well as economic and social damage (Kumar & Havey, 2013; Scholten, Sharkey Scott, & Fynes, 2014). Their response requires the establishment of supply chains to distribute aid (Steigenberger, 2016), however disaster response operation are inherently challenging due to characteristics such as unstable demand, increased urgency and high stakes (Ergun, Gui, Heier Stamm, Keskinocak, & Swann, 2014; Holguín-Veras, Jaller, Van Wassenhove, Pérez, & Wachtendorf, 2012; McLachlin, Larson, & Khan, 2009). Disaster response operations are mostly comprised of logistics activities and therefore logistics is often the cause of either a successful or failed operation (Wassenhove, 2006; Yadav & Barve, 2016). International humanitarian organisations (IHOs) frequently outsource the logistics function to logistics service providers (LSPs) to avail of their resources and expertise (Burcu Balcik, Beamon, Krejci, Muramatsu, & Ramirez, 2010). This often requires the establishment of a new relationship among these actors who may have different objectives and backgrounds (Gadde & Hulthén, 2009). In order to perform effectively, coordination mechanisms are used to manage interactions between the actors in this relationship (Xu & Beamon, 2006; Gadde & Hulthén, 2009). However, coordination is difficult to achieve in a disaster response for many reasons such as the high-stress conditions and multitude of actors involved (Jensen & Hertz, 2016; Pettit & Beresford, 2009). Disaster response operations have often been criticized for their lack of effectiveness (Haavisto & Goentzel, 2015) therefore there is great potential for improvement (Jahre, Ergun, & Goentzel, 2015). This research aims to fully understand how these relationships are coordinated in such a challenging environment and how the coordination mechanisms used affect the service performance of the operations.
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Literature in the area of humanitarian logistics has risen immensely since 2005 as its importance in the response to the devastating Asian Pacific tsunami and Hurricane Katrina in the U.S.A. was acknowledged (Coles, Zhang, & Zhuang, 2017; Jahre et al., 2015; Wang, Wu, Liang, & Huang, 2016). However, the topic of coordination mechanisms in disaster response is still underdeveloped as compared to the commercial sector (Balcik, et. al. 2010). Minimising costs is often the driver for selecting appropriate coordination mechanisms in the commercial sector (Xu & Beamon, 2006), however in the case of disaster response, there are often higher stakes which may have an influence on the coordination mechanisms used. Indeed, most logistics research uses cost performance as an outcome indicator, whereas service performance research is lacking (Hsiao, van der Vorst, Kemp, & Omta, 2010). Although most humanitarian organisations outsource some part of their logistics services (Camilo, Gil, & Mcneil, 2015; Jahre et al., 2011; Wang et al., 2016), few efforts have been made to research the role of the logistics service provider in a disaster response (Vega & Roussat, 2015; Wang, Wu, Liang, & Huang, 2016). Further, much of literature on this topic has a particular focus on sudden natural disasters (Binder & Witte, 2007). Therefore, an attempt is made to shed light on opportunities for coordination in slow as well as sudden on-set disasters. This is important as the level of human suffering in terms of malnutrition and increased mortality is often greater in a slow on-set disaster than a sudden on-on-set disaster (OCHA, 2011).
This research aims to establish how IHOs and LSPs use different types of coordination mechanism while facing contextual challenges in disaster response operations, and how this vertical coordination affects the service performance of the operations.
Research Question
How do the coordination mechanisms used by IHOs and LSPs influence service performance in a disaster response?
Sub-questions:
How do coordination mechanisms used by IHOs and LSPs influence service performance in a sudden on-set disaster?
How do coordination mechanisms used by IHOs and LSPs influence service performance in a slow on-set disaster?
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environments and make operational decisions accordingly. This is important as effective response operations attract donor contributions (Oloruntoba & Gray, 2009), on which humanitarian organisations are heavily reliant (McGoldrick, 2011). Further, the fact that humanitarian logistics is so underdeveloped while also being extremely important provides a great opportunity for advancement in this area (Thomas, 2003). Identifying how coordination mechanism can influence the performance of future disaster responses is particularly important as the number of disasters worldwide are expected to increase in the future (Kumar & Havey, 2013; Wassenhove, 2006).
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2. THEORETICAL BACKGROUND
2.1 Service Performance
The main performance objective in a disaster response is a social one; to minimise deprivation brought about by the shortage of goods or services (Holguin-Veras, et.al. 2012). In order to minimise this deprivation, flexibility and speed are essential to optimise the delivery process (Saputra, Pots, de Smidt-Destombes, & de Leeuw, 2015; Scholten, Scott, & Fynes, 2010). Speed is necessary in order to reduce the level of human suffering involved (Holguín-Veras, et. al. 2012). Flexibility is another critical performance objective, as forecasting in this environment is extremely difficult and supply and demand are highly uncertain (Charles, Lauras, & Van Wassenhove, 2010). Therefore, flexibility is necessary in order to provide agility, which in turn leads to a positive performance in a disaster response (Kabra & Ramesh, 2016; Scholten et al., 2010).
2.2 Sudden and Slow On-Set Disaster Response
Most literature on the topic of humanitarian logistics stresses the challenging nature of disaster response (Overstreet, Hall, Hanna, & Kelly Rainer, 2011). Because of these challenges, the coordination of all actors in a disaster response is extremely important (Kovács & Spens, 2007) as it manages the interactions in the relationship which is critical for the outcome of the logistics arrangement (Gadde and Hulthen, 2009). Therefore, this research will identify challenges for each type of disaster and how coordination mechanisms can aid in providing a fast and flexible response when faced with these challenges. Disasters can be categorised by the speed of on-set and source (van Wassenhove, 2006) as shown in table 2.1 below. Particular types of disasters can be associated with certain geographic regions, such as New Zealand and Japan being prone to sudden on-set disasters such as earthquakes, whereas the African continent suffers from many slow-onset disasters as a result of armed conflict (Kovács & Spens, 2009). Speed of on-set will be used for this research as this impacts response activities (Holguín-Veras et al., 2012).
Table 2.1 Disaster Categorization (Adapted from van Wassenhove, 2006; UNISDR, 2017)
Sudden On-set Slow On-set
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A sudden on-set disaster “is triggered by a hazardous event that emerges quickly or unexpectedly” (UNISRD, 2009). This type of disaster usually entails extremely chaotic environments (Thomas, 2003) as the post-disaster environment often contends with interrupted infrastructure, making transportation and other logistics activities more difficult (Beamon & Balcik, 2008; Tatham & Houghton, 2011). Another challenge is urgency, as delays in sudden on-set disaster response will have much more serious consequences than delays in commercial logistics (Overstreet et al., 2011). This urgency may even leave coordination mechanisms to be disregarded as they may not be considered a priority (Jensen & Hertz, 2016). Another challenging aspect of sudden on-set disaster response supply chains is the unpredictable nature of the event, which is an issue as resources and capacity become needed unexpectedly (Kumar & Havey, 2013; Yadav & Barve, 2016). In a sudden on-set disaster, coordination is often a problem because of these challenges(Nurmala, de Leeuw, & Dullaert, 2017) A slow on-set disaster can be defined as “one that does not emerge from a single, distinct event but one that emerges gradually over time, often based on a confluence of different events” (OCHA, 2011:3). A failure to recover from one event leaves the population more vulnerable to the next, therefore a coordinated early response is necessary in order to reduce this cycle of vulnerability (OCHA, 2011). Slow on-set disasters generally provide more time for preparatory activities as compared to sudden on-set disasters (Leeuw, Vis, & Jonkman, 2012). However, a perceived lack of urgency may pose a challenge (Jimenez Alonso, 2017) as a less dramatic disaster often leads to a lack of media attention (IRIN, 2012), and in turn, funding (Hurt, 2014). Further, contextual challenges in slow on-set disaster response can have a huge effect on the response operation, for example, security is an added complexity for all involved in a civil conflict (Stephenson & Schnitzer, 2006).
2.3 Coordination Mechanisms in a Disaster Response
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making and contracting (Simatupang Wright, & Sridharan, 2002; Daudi, Hauge, & Thoben, 2016; Arshinder, et. al. 2008).
Information sharing enables visibility that may ease logistics planning and execution and can be facilitated by tools such as I.T. (Simatupang et al., 2002). Information sharing is important to coordinate interdependent activities and support flexibility in challenging situations (Gadde & Hulthen, 2009; Liu et al., 2015), however accurate information can be quite limited in a disaster response environment (Sheu, 2007). Further, donor contributions tend to discourage investments in indirect capabilities or coordination tools such as IT systems which may hinder information sharing (Balcik & Beamon, 2008; Kopczak & Thomas, 2005; Scholten et al., 2010; McGoldrick). Moreover, a disaster response often generates competition among IHOs for donors, which may make them unwilling to share information (Altay & Pal, 2014; Coles, et.al, 2017). In a commercial environment information sharing often increases in line with business complexity (Welker, van der Vaart, & van Donk, 2008), however increased information sharing in a disaster response may be difficult for the above mentioned reasons. Joint decision making allows for synchronisation of interdependent activities (Simatupang et al., 2002). Joint decision making is different in disaster response compared to the commercial sector as the interactions are non-structured and carried out by many, as opposed to the structured interactions held between a few decision makers (Holguín-Veras et al., 2012).However, in a turbulent commercial environment joint-decision making between partners can introduce delays (Chatterjee, 2004), which is comparable to a disaster environment as decisions will need to take place quickly, and joint decision making may even impede performance (Charles et al., 2010; Nolz, Doerner, & Hartl, 2010). Contracts are put in place to manage the risk and the relationship between actors (Arshinder, Kanda, & Deshmukh, 2008). Designing contracts that are in the best interests of all parties is difficult in an environment prone to disruption (Giri & Sarker, 2017), therefore these contracts may need to become more flexible (Balcik, et. al. 2010). In a disaster response, contracts are typically referred to as frame-work agreements, of which little has been researched in literature (Balcik & Ak, 2014).
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adapting to contextual challenges. This is in line with the findings of Jahre, Ergun & Goentzel (2015), who state that a modular approach to standards tools is necessary.
As many IHOs and LSPs typically engage in both sudden and slow on-set disasters (Jahre et al., 2016), identifying the similarities and differences between them will allow actors to recognise the most appropriate coordination mechanisms for each disaster response type. As the choice of coordination mechanisms in a disaster response must consider the characteristics of the operating environment (Balcik et al., 2010), this research aims to establish how coordination mechanisms are implemented in slow and sudden on-set disaster response and how this affects service performance in terms of speed and flexibility. Figure 2.1 illustrates these concepts in a conceptual model.
Figure 2.1 Conceptual Model
Disaster Response Environment
Disaster Response Environment
Service Performance
Speed
Flexibility Coordination Mechanisms
Information Sharing
Joint Decision Making
Contracts/Framework Agreements
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3. METHODOLOGY
3.1 Research Design
Case research is the methodological approach chosen as it considers the context of the phenomenon under study in its natural environment without experimental manipulation (Meredith, 1998; Verschuren, 2003). As case research works well in a complex environment (Stuart, McCutcheon, Handfield, McLachlin & Sampson, 2002) this is especially suitable as disaster response operations are extremely complex due to factors such as unpredictability, urgency and political volatility (van Wassenhove, 2006). Case research is useful for extending existing theory and studying emergent practices (Voss, Tsikriktsis, & Frohlich, 2002). As we know that coordination mechanisms play an important role in increasing performance (Xu & Beamon, 2006), this research will further elaborate on the appropriateness of coordination mechanisms in different settings. This is important as there is significant room for improvement in humanitarian logistics (Thomas, 2003). As the research questions are “how” questions, case research is also particularly appropriate (Meredith, 1998). A multiple-case study approach is used as the results are generally considered more robust than a single case-study which increases the external validity of the results (Blumberg, Cooper & Schindler, 2013; Voss et al., 2002). Also, multiple case studies allow for the phenomenon to be viewed in different settings which allow for researching coordination mechanisms in both sudden and slow on-set disaster types.
3.2 Research Context
The research context is the disaster response. This will be looked at in different settings: sudden on-set, slow on-set and both. As many IHOs work in both disaster types (Jahre et al., 2016), this will allow for the research to be generalised to organisations that work in each disaster types and both. Using this context will allow the research question to be answered as the specific challenges faced in both disaster types can be identified.
Case Selection
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features of disaster type are identified, but also allowed overlapping features to be identified. Further, as the scope and difficulty of coordination implementation differ per organisation and the roles that they play (Jahre et al., 2011), the perspective of both the service provider and customer were used to determine the differences between the two. Therefore four cases have been chosen to investigate as shown in table 3.1 below, which fits with the recommendation of Eisenhardt (1989) of between four and ten. These organisations remain anonymous throughout the research to ensure confidentiality. The cases are representative of organisations types that are established in disaster response operations, therefore all organisations have been working in disaster response for more than ten years. This ensures that the coordination mechanisms they use are established within the organisations.
Table 3.1 Purposeful Sampling Disaster Setting Sudden on-set
Disaster Response
Slow on-set Disaster Response
Slow and Sudden on-set Disasters Organisation Type IHO Case A “Sudden Buyer” Case B “Slow Buyer” Case C “Buyer All” LSP Case D “Provider All”
3.3 Data Collection
Before collecting data, an interview protocol was developed which details the procedure for arranging interviews, the interview and post-interview (Stuart, Mccutcheon, Handfield, Mclachlin, & Samson, 2002). An interview questionnaire was developed based on the variables in the conceptual model. Two versions of the interview questionnaire have been made, one for the IHOs and another for the LSPs. These are identical apart from adjusting the perspective to service buyer or provider. In this manner, the interviews were all carried out similarly which helps with the reliability of the research (Yin, 1994). A pilot interview was held with a logistics coordinator with experience working in a disaster response in order to examine the viability of the interview protocol and questionnaire (Karlsson, 2016). This identified some questions which were too ambiguous and therefore adjusted accordingly before interviews began.
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The response rate was high with over half replying within five days. The next step was further explanation of the research and confirmation of their job status. The interview questionnaire was also provided. At this stage, many felt they did not have relevant experience to answer the questions. These respondents were then asked if they had colleagues who may be suitable to interview and these colleagues were contacted where possible. For the respondents that had fitting experience and accepted the invitation, an interview date and time was arranged. Due to the nature of their job, respondents were mainly based in disaster response operations internationally; therefore the most appropriate method to hold the interview was through Skype. This allowed for a wide geographic reach of interviewees. Semi-structured interviews were held so that the interviewee could elaborate on the answer given (Barratt, Choi, & Li, 2011). The interviewees working for IHOs were mainly logistics officers, project leaders and procurement coordinators. The interviewees working for LSPs were humanitarian affairs officers and logistics officers who have experience working in disaster response environments. All interviews were recorded and transcribed afterwards, which the interviewees were made aware of beforehand. The initial fifty requests elicited nine interviews, including the pilot interview. Thereafter, fifty more requests for interviews were sent out in the same manner leading to eight more interviews. The third round of requests resulted in four more interviews. Triangulation of evidence was done by carrying out two more interviews with experts in disaster response, one providing logistics training in disaster relief environments and the other an intermediary connecting IHOs and LSPs in disaster response operations. Interviews ranged in length from 31 to 75 minutes. The organisation’s websites were reviewed to ensure reliability by checking the services supplied and provided matched with the interviewee’s response. Interviewees were sent a transcript of the interview in order to confirm correct interpretation. Some interviewees were contacted during the analysis stage to clear up misunderstandings in the transcripts.
3.4 Data Analysis
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attached to one second order code became very large, this often resulted in the further categorization of the codes. Where second order codes had only one in-vivo code attached to them, they were disregarded or merged with other second order codes where appropriate. Next, these second order codes were grouped into more abstract 3rd order themes. These themes were partially discovered through the network view function, which allowed for an illustration of all second order codes and their relationship with each other. The next step was comparing the third order themes and interpreting the relationship between them. This process was followed for each case to gain familiarity with the data (Eisenhardt, 1989). After these within-case analyses were complete, a cross-case analysis was carried out in order to compare and contrast the results of the four cross-cases. The primary document table function allowed comparison of codes in different documents for the cross-case analysis in order to compare the results and allowed for pattern-matching. Cross-cross-case analysis and pattern matching were important to establish generalizable conclusions (Voss et al., 2002). Having a documented process throughout the data collection and analysis process allowed for a chain of evidence to be established (Stuart et al., 2002). Table 3.2 and table 3.3 below display the operationalisation of constructs and the coding structure respectively.
Table 3.2 Operationalisation of constructs
Construct Definition
Coordination Mechanism
Information Sharing Effectively creating information visibility for logistics planning and execution (Simatupang et al., 2002)
Joint Decision
Making All actors involved have the opportunity to be involved in the decision
Contracts(Framework agreements)
Agreement to deliver goods/service according to pre-specified terms once activated (Balcik & Ak, 2013)
Service Performance
Speed Time between beginning of operations and its end (Slack & Lewis, 2011)
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Table 3.3 Coding Structure:”Sudden Buyer”
Coordination Mechanism
First Order Descriptive Code Second Order Interpretive Theme Third Order Pattern Theme Information Sharing Interview 1 Interview 2 Interview 3 We share requirements in advance of operations (1:14)* We have meetings from the beginning (3:10) Early Requirement sharing Preparedness Orientation is given when provider has
been initially contracted (1:24) Quick orientation Feedback given to LSP (2:25) Feedback to LSP Seeking Improvement We use the expert advice of our LSP (2:23) Advice from LSP There is a quick Feedback lead time from LSP (2:12) LSP contact IHO when going beyond agreement (3:7) Quick Feedback from LSP
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4. RESULTS
In order to answer the research questions, contextual challenges present for each case are first identified and subsequently, the coordination mechanisms that are used and their influence on service performance are discussed. Each within case analysis is presented individually before a cross-case analysis is carried out.
4.1 Sudden Buyer
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Table 4.1 Results Overview – Sudden Buyer
Challenge Interview Number Coordination Mechanisms Influencing Service Performance Sub-groups 1 2 3 Access to Beneficiaries
Infrastructure damage x x n/a (+) Feedback and Advice Information Sharing Safety issues due to weather x n/a x n/a
Difficult terrain x n/a x (+ )Feedback and Advice Information Sharing
Lack of Resources and Capacity
Price spikes by service provider
n/a x x n/a
No warehouse available in disaster zone
n/a x x n/a
Labour availability x x n/a n/a LSP capacity limitations x n/a n/a n/a Communication
Infrastructure damage
x n/a x n/a
Authorization
Political interference x x n/a n/a
Government power x x n/a n/a
Funding Donor supply budget x n/a n/a n/a
Urgency
Time pressure x x x (+) Early requirement sharing: (+) Swift orientation process: Information Sharing
(+) Short-term contracts: (+) Open long-term contracts: Contracts
Unpredictability Unpredictability x x n/a n/a x: Identified challenge
n/a: Not identified
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4.2 Slow Buyer
This case consists of two UN agencies and six non-government organisation (NGOs) that provide aid in slow on-set disaster situations. Five of these organisations are involved in response operations to the ongoing war in Syria and the respective refugee crisis throughout Europe. The remaining three are responding to war in South Sudan and West Africa, therefore conflict was an issue most organisations were dealing with. Services provided include WASH (Water, Sanitation and Hygiene) programs and distribution of food and healthcare facilities. Outsourced logistics services include warehousing, air and land transportation, fleet management and customs clearance. Local LSPs are used where available as IHOs are eager to promote the local economy, however in some circumstances this was not possible, therefore international LSPs were used. The major challenge identified in this case is the lack of access to beneficiaries due to damaged/poor infrastructure and security reasons. This delay in access often had disastrous consequences where the situation was urgent.
“We couldn’t ship blankets because there was a conflict on the border so we couldn’t risk the lives of our staff, then when we got there people were frozen to death”. Interviewee 4
Another common challenge is the lack of resources and capacity necessary. This stems from a lack of employees as well as economic conditions where local markets are susceptible to monopolies and corruption is often accepted as the norm. This is often further exasperated by the huge fluctuations in local currency value due to the political turmoil. Some organisations were forced to accept these conditions in order to make use of the LSP’s services, as this was necessary in order to deliver aid to beneficiaries. There is also a safety issue as distributing aid may attract armed groups or even beneficiaries themselves being dangerous. In regards to coordination mechanisms, information sharing is seen in the form of basic transactional information about the service requirements from IHO to LSP. This information is shared through e-mail and phone with some use of Skype for conference calls. LSP’s local knowledge, networks and years of experience is a reason to share information further as LSPs often had more information about the security situation and access than IHOs. Their advice was an advantage as LSPs knowledge of regulations in terms of customs imports, border crossing and legislation issues allowed for a quicker response. Therefore, information sharing was mainly transactional from IHO to LSP and advice provided from LSP to IHO. Joint decision making is situation dependent in this case. No standard procedure is used and IHOs mainly make all decisions for basic operations. However, LSPs become more involved in decision making when the situation grows more complex.
“The more complicated and dangerous the environment, the more the decision will become shared” Interviewee 5
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Table 4.2 Results Overview- Slow Buyer
Challenges Interview Number Coordination Mechanisms
Influencing Service Performance
Sub-groups 4 5 6 7 8 9 10 11
Resources/ Capacity
Insufficient internal and external resources
n/a n/a x n/a n/a x n/a n/a n/a
Insufficient internal and external capacity
n/a x x n/a x n/a n/a n/a n/a
Local markets
monopolies/Corruption
x x n/a n/a x n/a n/a x n/a
Currency fluctuations n/a n/a x n/a n/a n/a n/a n/a n/a
Funding Delays from donors x n/a n/a x n/a n/a x n/a (-) Framework agreements restricted by donors:Contracts
Authorization
Legislation issues x n/a x n/a x n/a x n/a (+) Advice: Information Sharing
Border crossing x n/a x n/a x n/a x x (+) Advice: Information Sharing
Safety
Aid distribution can attract armed groups
x n/a n/a n/a n/a n/a n/a n/a n/a
Risk of beneficiaries having PTSD
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Challenges Sub-group 4 5 6 7 8 9 10 11 Coordination Mechanism
Influencing Service Performance
Access to
beneficiaries
Security x x x x x x x x (+) Advice: Information Sharing
Poor/ damaged infrastructure n/a n/a x n/a n/a x x x (+ )Advice: Information Sharing
Unpredictability Fluctuating demands x n/a x x n/a x n/a x n/a
Urgency Tight deadlines x x n/a x n/a n/
a
n/a n/a
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4.3 Buyer All
This case consists of four international IHOs that work in sudden and slow on-set disaster response operations in countries such as Haiti, South Sudan, Nepal, Zambia and Ethiopia. These disasters include, but are not limited to earthquake, flooding, drought and civil conflict. A mix of humanitarian and commercial logistics services are used and services provided consist of warehouse storage, sea and land transportation, fleet management, inventory management and customs clearance. Local LSPs are preferred where possible for convenience and to contribute to the local economy; however, some international LSPs are used where necessary.
The main challenges faced in this case are access to beneficiaries and lack of adequate resources and capacity. Lack of access to beneficiaries is due to security issues and poor/damaged infrastructure. Lack of resources and capacity is caused by many factors; airport congestion, corruption, border closures and damaged infrastructure. Funding is also an issue, particularly in slow on-set disasters. “We call them slow on-set disasters, whereby we know that there are issues, but we can only deal with them based on funds available to us” Interviewee 12
Coordination in terms of information sharing is situation dependent. Many logistics operations require only transactional information although the situation can sometimes become more complex due to the issues such as local conflict. This is when the LSPs can provide advice as to the best method of delivery as most LSPs have a long experience working in the humanitarian sector. Communication methods used are mainly phone, e-mail face to face meetings. Joint decision making is also seen in different forms. There is a level of trust in LSPs to make a decision on the behalf of the IHO in order to save time or where IHOs don’t have access due to restrictions, therefore joint decision making is not necessary. However, IHOs feel accountable to their donors who restrict LSPs influence on decisions to some degree as they want full control over the supply chain and sometimes are not willing to trust their LSP entirely. In terms of contracts, all agreements were in place in an attempt to improve flexibility and speed, such as stand-by agreements, rolling framework agreements and non-binding contracts. These contracts are often put in place before the disaster response or before they are needed during a disaster and can be adapted to different contexts and needs which allow for a quicker process when they are needed. Many IHOs know LSPs from previous experience; therefore, there is often a long-term informal relationship. The positive influence of long-term, personal relationships is also shown in this case as interviewees felt personal relationships allowed greater flexibility and understanding of the ultimate objectives.
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Therefore, service performance is improved through LSPs sharing their expertise and contracts that are designed to be flexible. Joint decision making influences service performance both positively and negatively. Trust in the LSP to make decisions on behalf of the IHO generally allows for a more flexible operation; however, the accountability they have to their donors restricts trust, therefore joint-decision making can reduce flexibility. An overview of these results can be seen in table 4.3 below.
Table 4.3 Results Overview –Buyer All
Challenges Interview Number
Coordination Mechanisms Influencing Service Performance Sub-group 12 13 14 15 Access to beneficiaries Poor/damaged infrastructure
x n/a x x (+)Advice: Information Sharing
Security Restrictions
n/a n/a x x (+)Advice: Information Sharing
Poor terrain x n/a n/a n/a (+)Advice: Information Sharing
Resources/ Capacity
Corruption n/a n/a x x n/a
Border Closure n/a n/a x n/a n/a
Airport congestion
n/a x n/a n/a n/a
Communication infrastructure
downstream
n/a x x x n/a
Funding Donor restrictions n/a n/a x n/a (-) Lack of Trust: Joint Decision Making
Authorization Border closures/supply
disruptions
n/a n/a x n/a (+)Advice: Information Sharing
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4.4 Provider All
This case consists of two large commercial LSPs and two LSPs who regularly work with humanitarian organisations on a cost recovery basis. These LSPs work internationally in locations such as Nepal, Haiti, and Africa. Services provided range from providing procurement services to last mile delivery and they typically have partnerships with large international IHOs.
A major challenge recognised in this case is the lack of competence of IHOs. This is due to a long chain of command within IHOs, a lack of logistics expertise and a stove-pipe mentality, where each IHO is focused on their individual objectives rather than the collective disaster response objective. In this situation, LSPs can share their advice with their IHO partner as they are more experienced. Also, they try to share information between IHOs that are involved in a disaster response in an effort to make operations more efficient. Other challenges faced by these LSPs were mainly access to resources and authorization. Although these organisations often faced difficulties accessing certain areas because of conflict or damaged infrastructure, their expertise allowed them to adapt quickly to these situations. All LSPs in this case have worked in a variety of disaster situations and therefore have the advantage of experience. Although some of the LSP offer commercial services, they mainly also share humanitarian goals of saving lives, therefore LSPs offer not only their resources but also like to provide value-added service. There is a sense of empathy that leads to LSPs wanting to add extra value in any way they can. Therefore information-sharing is done through providing advice where it is requested.
“When they look for our advice, we can provide the best alternatives” Interviewee 15
Primary communication methods are phone, e-mail and Skype although it is noted that these methods are determined by their partner’s capabilities.
“We could potentially have an ERP system, we could get it to work decently in a very short space of time, but I don’t think you will have that happening in Chad or Central African Republic, because your counter-parts will not have an ERP system, you are lucky if they have a computer” Interviewee 16
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Table 4.4 Results Overview- Provider All
Challenges Interview Number Coordination Mechanisms
Influencing Service Performance Sub-groups 16 17 18 19 20
Resources Suitable equipment
x x x n/a n/a (+ )Advice: Information Sharing
Lack of competence IHOs
IHO lack of expertise
n/a x x n/a x (+)Advice: Information Sharing
IHO Stove-pipe mentality
x x x n/a n/a (+) Coordinate between IHOs: Information Sharing
Long chain of command
n/a x x n/a n/a
(-) Waiting for decision: Joint Decision Making
Access to beneficiaries
Destroyed infrastructure
n/a n/a x n/a n/a (+) Advice: Information Sharing
Security
n/a n/a x x x (+) Advice: Information Sharing
Authorization
Trade limitations and
cargo bans
n/a x x n/a n/a (+) Advice: Information Sharing
Government Regulations
n/a x x n/a n/a (+) Advice: Information Sharing
Unpredictability Unstable demand
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4.5 Cross-Case Analysis
The main challenges recognised in all four cases are very similar. All organisations find it difficult to access beneficiaries, source adequate resources and capacity and have problems with authorization. Even though performance is rarely measured, results suggest that speed is the most often sought after performance objective for all four cases, even prioritised above cost. Sudden buyer, slow buyer and buyer all felt their actions were accountable to their donors and so ensured they had more control over decision making processes. They also generally restrict information sharing to transactional information where possible although the advice of their LSP is used where the situation becomes more complex. Across all four cases, there are no standardised information sharing or joint decision making processes in place as they are highly dependent on the requirements of the situation. Information sharing methods in all cases are quite basic with telephone and e-mail as the primary methods of communication. Although all organisations acknowledged urgency as a challenge, all cases are generally prepared for these urgent situations. This is reflected in the use of standard rolling, non-binding or open framework agreements in all cases. The types of relationships seen across all four cases tend to be both formal in the short term, such as a contract for a specific response, and informal in the long term as personal relationships grow from previously working together.
29 Table 4.5 Results Overview- Cross-case
Coordination
Mechanism Sudden Buyer Slow Buyer Buyer All Provider All Influence on Service Performance
Information Sharing Type Transactional Requirement sharing Orientation Advice Feedback Transactional Advice Feedback Transactional Advice Feedback Transactional Advice Feedback
Influences speed and flexibility positively through expertise of LSP and early information sharing
Information Sharing Method
Phone & E-mail Phone, E-mail and Face to face meetings
Phone, E-mail and Face to Face meetings
Phone, E-mail and Skype
Joint Decision Making
High involvement in decision making, LSP make decisions where needs arise
Not necessary day-to-day
More complex operations call for involvement of LSP in decisions Dependent on trust of LSP and accountability to donors Low involvement in decision making
Negative influence on speed and flexibility: Accountability to donors restrict trust in LSP to make decisions
Contracts
Short- term per job order basis locally
Long-term open contracts internationally
Yearly rolling
Framework agreements Short term locally Long term internationally
Stand-by agreements Rolling framework agreements
Short term locally Long term internationally
Standardised framework agreements
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5. DISCUSSION
5.1 Summary of Findings
The research set out to discover how the coordination mechanisms used by IHOs and LSPs influence the service performance in a disaster response. The findings verify much of the research initially discussed. The performance outcome of the outsourcing arrangement is highly influenced by the nature of the relationship between IHO and LSP (Gadde & Hulthén, 2009), in particular relationship length. The type of relationships between IHOs and LSPs tend to be both formal in the short term, such as a contract for a specific response, and informal in the long term as personal relationships grow from working together (Hertz & Alfredsson, 2003). Therefore personal relationships are common between IHOs and their international LSPs, whereas short-term formal relationships are common from national distribution centres to delivery point. Working together long term often leads to relationship development, shared networks and better performance in general. The advantage of the personal element of relationships cannot be underestimated. In terms of coordination mechanisms, the findings support previous research that information sharing and contracts support speed and flexibility. Information sharing allows greater visibility, in particular, advice flowing from LSP to IHO. Nevertheless, shared I.T. systems are virtually non-existent and in most cases not viable due to poor infrastructure and donor contributions restricting funding for indirect resources (Aflaki & Pedraza-Martinez, 2016). Framework agreements are designed with speed and flexibility in mind; they are straightforward and adaptable to the needs of the situation (Balcik et al., 2010). Joint decision making is, as previously speculated, non-structured and carried by many (Holguín-Veras et al., 2012) which often leads to delays in the operation. In terms of disaster type, findings imply that slow and sudden on-set disasters share most of the same challenges. Although slow on-set disasters are usually ongoing over a number of years, urgent situations within the overall disaster response frequently occur and therefore similar coordination mechanisms are used as for sudden on-set disasters. Security is seen as a major issue for slow on-set disasters as most were conflict situations. Results also show that logistics services in different kinds of disasters are very similar (Camilo et al., 2015), therefore it is possible for IHOs to use the same LSPs for different disaster types.
31
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5.2 Implications for Research
The original research gap was in relation to coordination practices between IHOs and LSPs in slow and sudden disasters. This research provides insights into the different challenges faced by IHO and LSP in a disaster response, and also aspects that can be used to enhance performance in the future. The long term nature of a slow on-set disaster allows local LSPs time to adjust to the situation and therefore become highly valuable to IHOs. Further, although shared I.T. systems are generally not available due to limited finance and poor/damaged infrastructure, this does not seen to be an issue for communication.
5.3 Implications for Practice
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6. CONCLUSION
This paper has examined the influence of coordination on service performance in different disaster response settings. The findings confirm that coordination plays a key role in service performance, and although this role is acknowledged by the actors involved, often underused due to the environmental challenges faced. The research identified challenges in slow and sudden on-set from the point of view of both IHO and LSP. The challenges are similar for both disaster types, whereas the challenges for organisation types differ..
Naturally there are some limitations to this research which must be taken into consideration. It was not possible to research dyadic relationships between LSP and IHO within the time constraints. Therefore this research can only compare both perspectives and generalise the findings rather than discovering direct influences they have on each other. Further, the slow on-set disasters studied were all conflict related, therefore this limits the generalizability of the findings. Also, LSPs interviewed provide international services, therefore the perspective of local LSPs is not considered. Moreover, the coordination mechanisms were deemed appropriate for this context, although there are many different types of coordination mechanisms that may affect the results differently.
Future research in dyadic relationships between IHOs and LSPs may lead to an even deeper understanding of direct interactions between them. Further, research using humanitarian supply chains could be used as the unit of analysis rather than single organisation types in order to further investigate coordination among a number of actors. There is also further opportunity for research in the last mile delivery stage as it can often be the most complicated stage of the operation (Oloruntoba & Gray, 2006). Also a number of different coordination mechanisms could be researched, such as standardization or collaborative procurement. These topics should reveal new insights into coordination in disaster response operations.
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APPENDICES
Appendix A - Interview Protocol
Before interviewExplain purpose of the research to interviewee
Confirm job position and relevant experience of interviewee Send interviewee questions to allow for reflection
Arrange date and time and swap Skype id
During interview
Ensure interviewee is aware the interview will be recorded
Ensure interviewee is aware final research will be made anonymous Begin recording of conversation
Introduction to the research intention
Follow question list and probe for further information where applicable
After questions have been asked, inquire about further insights that may not have been covered in the question list.
Inform interviewee of expected time frame of results
Add name to list of interviewees that would like to receive final research
After interview Transcribe recording
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Appendix B - Interview Questions
Version 1: Logistics Service Provider
_____________________________________________________________________________
The Influence of Coordinating Logistics Services on Service Performance in Slow and
Sudden On-set Disaster Response
The following questions are regarding your organisation providing logistics services for humanitarian organisations in disaster response environments.
The interview will be recorded for transcription purposes only. All answers will be treated confidentially and be exclusively used for the purpose of this research at the University of Groningen.
Thank you for your time.
General Background of organisation
1. Can you briefly give a short background of the organisation you work/worked for? 2. How long have you been working /worked with this organisation?
3. What is your position with your organisation?
Disaster Response Challenges 4. What type of disaster does your organisation work in?
5. What is particularly challenging about these environments, in terms of delivering relief? 6. Is the demand for relief generally stable?
7. How urgent were/are the demands for relief? (e.g. needed the next day, long term demands, etc). What is/was the reason for the urgency?
8. Is infrastructure generally disrupted in this environment? (e.g. destroyed roads, bridges, electricity outages, etc.)
Logistics Services
9. Are the logistics services you provide commercial or donated?
10. For how long have you provided logistics services for humanitarian organisations? 11. What is the nature of the service provided?
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Coordination Mechanisms
13. Do you use information sharing for coordinating with humanitarian organisations? If yes, how do you implement information sharing?
How does this information sharing facilitate your performance in terms of speed and flexibility?
14. Do you use joint decision making with the humanitarian organisation and if yes, how do you use it?
How does this joint decision making facilitate your performance in terms of speed and flexibility?
15. Do you use contracts when coordinating with your humanitarian organisation? If yes, what sorts of contracts are used?
How do these contracts facilitate your performance in terms of speed and flexibility? 16. What role do the disaster response challenges (as mentioned in question 5,6,7,8,) play in
deciding how to coordinate?
17. Is there any other type of coordination used when outsourcing to this logistics service provider?
Performance Outcomes
18. How does/did your organisation measure performance outcomes?
19. How important are speed and flexibility to your operations in general? (Are other performance outcomes more important?)
20. What is/was your logistics services contribution to the speed and flexibility outcomes of the humanitarian organisation?
In Summary
-Are there any other issues that arise in a disaster response environment which were not mentioned here? Particularly regarding coordinating with humanitarian organisations and the service performance outcomes of this arrangement?
