The role of social micro hubs in the
e-commerce last mile
A case study
Final Version
28-01-2019
Master Thesis Msc. Supply Chain Management
University of Groningen – Faculty of Economics and Business
Thesis Supervisor: Prof. Dr. K.J. Roodbergen Thesis Second Assessor: Dr. M.J. Land
Author: Tristan Brouwer (s2463210)
Acknowledgment: I would like to express my gratitude towards the people without whom
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Abstract
Purpose – This research studies the logistical role of social micro hubs in e-commerce last mile
parcel delivery. Social micro hubs are a new concept of service points for the receiving, delivering and sending of parcels in a residential area at a residential premise.
Design/methodology/approach A single case study approach has been used. Interviews have
been conducted with four identified relevant stakeholders in the last mile: senders, freight carriers, administrators and consumers.
Findings – This study found that social micro hubs can be of added value in an e-commerce to
consumer supply chain. Social micro hubs can increase efficiency in the last mile by increasing the use of efficient linehaul transport, decreasing pick-up and delivery costs and decreasing hub-operating costs. It can also have a positive impact on the consumer experience. Important aspects are the ambiguity towards opening times for consumers, the reliability of the system, and the return logistics.
Research implications/limitations – Future research on social micro hubs in different contexts
should be conducted to increase generalizability of the results.
Originality/value/contribution – This study lays the groundworks for research on social micro
hubs by defining the role of social micro hubs in last mile delivery.
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Table of Contents
Abstract ... 2
1. Introduction ... 4
2. Literature Review ... 6
2.1 Defining the last mile ... 6
2.2 Stakeholder groups ... 7 2.3 Design factors ... 8 Sender ... 9 Freight Carrier ... 10 Consumer ... 11 Administrator ... 12 3. Methodology ... 13 3.1 Data Collection ... 14
3.2 The Case Study ... 15
3.3 Data analysis ... 16 3.4 Coding Tree ... 17 4. Findings ... 18 4.1 Efficiency ... 19 4.2 Consumer experience ... 20 Convenience ... 20 Opening times: ... 22 Safety ... 23 4.3 Social value ... 23 4.4 Reliability ... 24 4.5 Environmental effects ... 25 4.6 Design ... 25 4.7 Other aspects ... 26 5. Discussion ... 27 5.1 Non-unique factors ... 27 5.2 Unique factors ... 29 6. Conclusion ... 32
6.1 Directions for future research ... 33
References ... 35
Appendix A – Interview Guide ... 39
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1. Introduction
E-commerce worldwide is expected to more than double from 2016 to 2021 (Statista, 2018), while urbanization is predicted to grow to 70% in 2050 (United Nations, 2015). Consequently, an ever-increasing number of parcels have to be delivered to an ever-increasing number of homes in an area. Combined with a shortage of drivers in the logistics sector (DHL, 2018), it is becoming more difficult to deliver all packages to every single front door on time (NU.nl, 2018, 2017; RTL Z, 2017; Telegraaf, 2017). Many stages in the product supply chain have become more efficient over the last years, but the very last step in the delivery – bringing the parcel to the front door of the consumer – is often the least efficient, the most polluting and the most expensive part of the whole supply chain (Deutsch and Golany, 2018), with cost up to 28% of the whole transportation process (Goodman, 2005). Because of this, attention should be paid to the final part of business-to-consumer deliveries (Deutsch and Golany, 2018). A new concept in this last part is called social micro hubs and could potentially offer solutions to some of these problems.
This final leg in a business-to-consumer transaction, in which the parcel is delivered to the consumer’s home or a parcel collection point, is called the ‘last mile’ (Cardenas et al., 2017; Deutsch and Golany, 2018; Gevaers et al., 2011; Harrington et al., 2016). Although the term last mile is not restricted to e-commerce or parcel delivery (Deutsch and Golany, 2018), this paper only studies the last mile in an e-commerce to consumer setting, with delivery either at the home address of the consumer or at a parcel collection point, where the consumer can pick-up the parcel (Gevaers et al., 2011). Like Gevaers et al. (2011), this paper limits itself to the very last section of a supply chain, from the moment a parcel leaves the warehouse of a supplier or logistics provider. This will be analyzed from a supply chain perspective, including senders and freight carriers.
5 Many last mile solutions that try to solve (aspects of) the complexity of last mile deliveries have been studied. Examples of such solutions are lockers (Deutsch and Golany, 2018; Iwan et al., 2016; Vakulenko et al., 2018), light vehicles (Anderluh et al., 2017; Devari et al., 2017), and cargo bikes (Anderluh et al., 2017; Van Duin et al., 2013). Some of the studies on these solutions have investigated the logistical organization of these solutions (Iwan et al., 2016). However, to the best of knowledge, no literature has been written on social micro hubs. Previous research has identified aspects for last mile solutions that define the advantages and disadvantages of these solutions, so-called “design factors”. These design factors will be used in this research to assess the role that social micro hubs can play in last mile logistics. The “role” is defined as the way social micro hubs can aid in getting products from sender to customer in an effective and cost-efficient manner. Aspects such as efficiency, customer satisfaction, social value, and reliability will be discussed. Thus, the research question of this paper is:
“What can be the role of social micro hubs in the e-commerce last mile from a supply chain perspective?”
To answer this main research question, the following sub-questions will be used in this research: - What are existing last mile delivery alternatives to social micro hubs?
- Who are the logistical stakeholders in the last mile?
- What are the logistical needs of these stakeholders for the last mile? - What are logistical aspects that can be influenced by social micro hubs? - What are the logistical advantages of a social micro hub?
- What are the logistical disadvantages of a social micro hub?
- How does the logistical operation of a social hub benefit stakeholders?
These research questions will be answered by means of a single-case study. Identified stakeholders will be interviewed, and the results will be analyzed to create an overview of stakeholders, advantages and disadvantages of a social micro hub, and design factors relevant to a social micro hub.
6 where Vakulenko et al. (2018) focus on consumer value, this study takes a logistical view, in line with Deutsch and Golany (2018) and Anderluh et al. (2017).
Moreover, this research will add value for managers by providing design factors relevant to social micro hubs. For e-commerce retailers, it will provide an insight into the value of using social micro hubs as a last mile delivery option instead of conventional last mile solutions. For logistics service providers, it will present an overview of considerations when to choose for social micro hubs.
The remainder of this paper will be as follows: In Chapter 2, an overview of existing relevant literature will be given, including the definition of last mile delivery used in this research and the identification of the stakeholders in last mile solutions. In Chapter 3, the methodology of this research will be presented, and in Chapter 4 the results will be shown. Chapter 5 will discuss these results and their implications. Finally, Chapter 6 will present conclusions and the limitations of this research.
2. Literature Review
The literature review is structured as follows. First, the context of this research will be defined, describing the last mile as used in this research and specifying complexities related to the last mile. Next, stakeholders will be identified, followed by an analysis of existing last mile solutions to extract design factors which are potentially relevant for social micro hubs. These stakeholders and design factors will be used as the basis for the interview guide discussed in Chapter 3.
2.1 Defining the last mile
7 There are three main reasons for the expensiveness and complexity of last mile deliveries: First, the lack of economies of scale, as often only one package has to be delivered per destination address (Gevaers et al., 2011; Goodman, 2005). Secondly, time is wasted finding the home address of the recipient, or the long walk inside an apartment block (Gevaers et al., 2011). Finally, many recipients are not at home when the delivery attempt takes place, resulting in high delivery failure and empty trip rates (Gevaers et al., 2011; Loqate GBG, 2017).
2.2 Stakeholder groups
The following section will analyze the different stakeholders in the last mile, since stakeholders have to be established before design factors can be identified. Most literature about the last mile identifies at least the following stakeholders: sender, freight carrier, administrator and consumer, which is in line with Taniguchi and Tamagawa (2005). See also Table 2.1 for an overview of the stakeholders and the various terminologies used in literature. The identified stakeholders will be used to find design factors per stakeholder in existing literature in Section 2.3, and subsequently to determine appropriate interviewees for this research. Following, these stakeholders will be used to identify design factors for social micro hubs in Chapter 4, and to discuss implications of social micro hubs for each of the stakeholders in Chapter 5.
Stakeholder Terminology Sources
Sender E-commerce Parties (Deutsch and Golany, 2018)
Industrial (Harrington et al., 2016)
Sender (Taniguchi and Tamagawa, 2005)
Shipper (De Souza et al., 2014)
Freight Carrier Carriers (Muñoz-Villamizar et al., 2015)
Freight Carriers (Taniguchi and Tamagawa, 2005) Industrial (Harrington et al., 2016)
Logisticians (Cardenas et al., 2017) Logistic Service Providers (De Souza et al., 2014)
Consumer Consumer (De Souza et al., 2014; Harrington et
al., 2016; Taniguchi and Tamagawa, 2005)
Customer (Deutsch and Golany, 2018; Muñoz-Villamizar et al., 2015)
8 Authorities (Cardenas et al., 2017)
City Government (Muñoz-Villamizar et al., 2015) City Municipalities (De Souza et al., 2014)
Institutional (Harrington et al., 2016)
Public Administration (Muñoz-Villamizar et al., 2015)
Local Retailers Retailers (De Souza et al., 2014)
Shopkeepers (Muñoz-Villamizar et al., 2015)
Citizens Citizens (Cardenas et al., 2017)
Inhabitants (Muñoz-Villamizar et al., 2015)
Table 2.1 – Stakeholders in the last mile
The sender is the party sending the parcel, often an e-commerce retailer (Harrington et al., 2016). Although the sender can be anyone sending a parcel, this research will focus on e-commerce retailers as senders. This means that these terms will be used interchangeably in this research. Freight carriers are companies transporting parcels from the sender to the consumer (Gevaers et al., 2011), generally logistics providers. Administrators are local and regional authorities that have influence over the area that the last mile is located in. They also provide the infrastructure (e.g. road, rail, etc.) needed for goods transportation (Harrington et al., 2016). Consumers are the final recipients of the parcels and are the group that generally initiates the flow of goods from e-commerce companies due to their demand for products (Gevaers et al., 2011).
2.3 Design factors
In this section, existing last mile solutions will be analyzed to extract factors important in a last mile solution. Design factors for each of the stakeholders will be presented. According to Dolati Neghabadi et al. (2018), the most discussed types of innovative solutions in the last mile are off-hour deliveries and cargo cycles, and therefore these last mile solutions will be studied. Another intensively studied solution is collection-and-delivery points. These solutions will be studied due to the similar characteristics between social micro hubs and collection-and-delivery points.
9 center, or by temporary hubs, e.g. vans parked in a parking spot nearby the city center (Anderluh et al., 2017).
Collection-and-delivery points are locations at which consumers can collect and return parcels (Weltevreden, 2008). There are two types: retail service points and locker points (Weltevreden, 2008). A service point is a shop-in-shop concept; parcels are delivered to a store, petrol station, or post office where customers can pay, collect and return their parcel. At a service point, the store personnel manages the collection procedure (Weltevreden, 2008). A locker point is a group of lockers, the electronic locks of which can be opened with variable opening codes (Deutsch and Golany, 2018; Iwan et al., 2016).
In the following section, relevant factors from each last mile solution will be discussed in the light of the stakeholder to which it is important. The results of this literature background research are summarized in Table 2.2, where all identified design factors per stakeholder are shown.
Sender
Four important factors have been identified for senders in other last mile delivery solution that might potentially also be relevant to social micro hubs: differentiating, cost, customer loyalty, and customer satisfaction.
Differentiating from competitors can be achieved through logistics, especially since consumer preferences have moved to the center of attention (Joerss et al., 2016). This means that the last mile solution offered by the sender can be a tool to increase customer satisfaction.
Cost is another relevant design factor for senders in last mile solutions (Pelletier et al., 2016; Van Duin et al., 2013). Since generally the freight carrier is hired by the sender, efficiency and cost aspects are often transferred to the sender, aligning the interests of senders and freight carriers on an efficient delivery (Harrington et al., 2016). Because of this, the sender benefits from an efficient delivery process.
10 (2003, p. 125) as “the customer’s favorable attitude toward an electronic business resulting in repeat buying behavior”.
Customer satisfaction is one of the most important drivers for customer loyalty, because an increase in customer satisfaction can lead to an increase in customer loyalty, shown by increased likelihood of repeating purchases and decreased receptiveness for the offerings of competitors (Anderson and Srinivasan, 2003; Kasper, 1988; Torres-Moraga et al., 2008). Satisfied customers also are more likely to recommend others the source of satisfaction (Ganesh et al., 2000). Choice of last mile delivery method can influence the customer satisfaction of consumers (Thirumalai and Sinha, 2004).
Freight Carrier
Five design factors for freight carriers have been found: increasing scale, the not-at-home problem, total driving distance, cost per distance, range of vehicles, and use of public space. Increasing scale is the most important factor for making a profit for a freight carrier in the last mile (Harrington et al., 2016). Because a traditional e-commerce last mile has very limited scale possibilities, efficiency is low (Gevaers et al., 2011). The use of retail service points or lockers shows that it is possible and desirable for freight carriers to achieve some economies of scale in the last mile. By using retail service points or lockers as a delivery point, instead of the front door of the consumer, more parcels can be delivered to less delivery points (Deutsch and Golany, 2018; Weltevreden, 2008), enhancing performance and reducing last mile costs (European Commission, 2012; International Post Corporation, 2012).
The not-at-home problem can also be reduced with the use of retail service points or lockers (Deutsch and Golany, 2018; Gevaers et al., 2011; Iwan et al., 2016; Weltevreden, 2008), which reduces the number of seconds attempt deliveries.
11 Cost per distance, just like total driving distance, influences total costs. However, since electric vehicles are still expensive to purchase (Pelletier et al., 2016), often underperform compared to specifications (Van Duin et al., 2013), and have a limited range compared to combustion-engine driven vehicles (Pelletier et al., 2016), cost per distance can be higher than using traditional delivery methods.
Range of vehicles can be relevant to last mile solutions, as Anderluh (2017) discusses the limited range and capacity of cargo bikes as a disadvantage in the last mile, because it reduces efficiency.
Use of public or private space is also an important design aspect for freight carriers. When using lockers, public space is often necessary. This might encumber the rapid expansion of a locker network, since permits from local governments are necessary (Weltevreden, 2008). Moreover, a public location increases vulnerability to theft of parcels and vandalism (McKinnon and Tallam, 2003). Because of this, a last mile solution on public space might bring challenges, and private space might be favorable for a last mile solution.
Consumer
For consumers, four different design factors are distinguished: location, timeliness, social value and anonymity at pick-up.
Location is an important design factor, since it is one of the main advantages e-commerce retailers offer to consumers (Laudon and Traver, 2013). This is also the advantage that cargo bikes (Anderluh et al., 2017) and electric vehicles (Van Duin et al., 2013) offer: the parcels can still be delivered to the front door. Even when the parcel is not delivered to the front door, as is the case with lockers, consumers prefer the parcel to be delivered close to their home (Iwan et al., 2016).
Timeliness for consumers in the last mile process is crucial. One of the strengths of retail service points and lockers is the fact that parcels can be picked up whenever the consumer prefers, increasing service experience for consumers (Deutsch and Golany, 2018; European Commission, 2012; International Post Corporation, 2012; Weltevreden, 2008). Lockers have the extra advantage of larger opening times compared to retail service points so that consumers choice of timing is increased even further (Deutsch and Golany, 2018)
12 interaction at a last mile solutions, while others benefit from the lack of social interaction at lockers (Vakulenko et al., 2018).
Anonymity at pick-up might also be desired by consumers in a last mile solution. According to Weltevreden (2008), anonymity when picking up a parcel at a locker facility might be a necessity for some consumers.
Administrator
Three relevant design factors are found in literature for administrators: CO2 emission, noise
levels, and traffic congestion.
CO2 emission in an urban area is one of the design factors relevant to the institutional
stakeholder. One of the main advantages of electric vehicles is the reduction in CO2 production
(Pelletier et al., 2016; Van Duin et al., 2013). CO2 is also reduced when using cargo bikes
instead of combustion-driven vans (Anderluh et al., 2017). CO2 emission is the main
disadvantage of conventional delivery and off-hour delivery (Sathaye et al., 2010; Ukkusuri et al., 2015).
Noise levels in the urban area is the second design criterion important for the institutional stakeholder. Pelletier et al. (2016) report that a valuable advantage of the use of electric vehicles is the reduction in noise. Cargo bikes also provide a huge noise advantage compared with conventional delivery (Anderluh et al., 2017).
Traffic congestion is the third design criterion important for the institutional stakeholder. The main advantage of cargo bikes (Anderluh et al., 2017) and off-hour deliveries (Sathaye et al., 2010; Ukkusuri et al., 2015) is the reduction of traffic congestion. – bikes, because they are more flexible in traffic, and off-hour delivery, because it leads to a better division of movement of goods across the day. This leads to improved spread of traffic across the day, which results in a better traffic flow (Ukkusuri et al., 2015). Policy makers also see the potential of retail service points in reducing traffic congestion (OECD, 2003).
Stakeholder Design Factor Author
Sender Differentiating (Joerss et al., 2016)
Cost (Harrington et al., 2016; Pelletier et al., 2016; Van Duin et al., 2013)
Customer Satisfaction (Anderson and Srinivasan, 2003)
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Freight Carriers
Increasing scale (Deutsch and Golany, 2018; Harrington et al., 2016; Weltevreden, 2008)
Not-at-home problem (Deutsch and Golany, 2018; Weltevreden, 2008)
Total driving distance (Van Duin et al., 2013)
Cost per distance (Anderluh et al., 2017; Pelletier et al., 2016; Van Duin et al., 2013)
Range of vehicles (Anderluh et al., 2017; Pelletier et al., 2016) Use of public space (McKinnon and Tallam, 2003; Weltevreden,
2008)
Consumers Convenience (Anderluh et al., 2017; Iwan et al., 2016; Laudon and Traver, 2013; Van Duin et al., 2013)
Timeliness (Deutsch and Golany, 2018; European Commission, 2012; International Post Corporation, 2012; Weltevreden, 2008) Social Value (Vakulenko et al., 2018)
Anonymity at pick-up (Weltevreden, 2008)
Administrators CO2 Emission (Anderluh et al., 2017; Pelletier et al., 2016;
Sathaye et al., 2010; Ukkusuri et al., 2015; Van Duin et al., 2013)
Noise level (Anderluh et al., 2017; Pelletier et al., 2016) Traffic congestion (Anderluh et al., 2017; OECD, 2003; Sathaye
et al., 2010; Ukkusuri et al., 2015)
Table 2.2 – Design factors per stakeholder in the last mile
Table 2.2 provides an overview of identified design aspects per identified stakeholder in the previous section. In the remainder of the research, the identified design factors will be compared to design factors relevant to social micro hubs, which will be the result of the conducted interviews.
3. Methodology
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3.1 Data Collection
The unit of analysis is a social micro hub delivering system in its logistical context. The empirical data was gathered over a period of three months. First, a round of unrecorded, unstructured interviews were held, with the purpose of understanding the concept, and to get to know the companies involved in the social micro hub delivery network. These interviews took place in the first phase of the research with managers from three participating companies – one manager from the sender, one manager from the freight carrier, and the founder of the social micro hub company - representing two of the four stakeholders identified in Chapter 2. After the first round of interviews took place, a meeting with the same three managers and a logistical expert took place to present the research proposal, and to ensure the right interpretations of the first round of interviews.
In the second phase of the research, seven semi-structured interviews were recorded and transcribed. To enhance the reliability and validity, a research protocol was developed (Yin, 1994). Part of this research protocol were the interview guides, which can be found in Appendix 1. Interview guides were developed using a funnel method, starting with broad and open-ended questions, while more specific and detailed questions came last (Karlsson, 2016). The interview guides were developed using the stakeholders and design factors identified in Chapter 2. In this research, local retailers and citizens (i.e. citizens who do not receive parcels, opposed to “consumers”) are not discussed, because they do not actively participate in the last mile. The goal of the interviews was to find out if identified criteria as found in Chapter 2 are relevant in a social micro hub setting, and if additional unidentified design factors play a role in this setting. This resulted in the coding tree explained in Chapter 3.4. As such, questions were created to cover each of the design factors, and to identify additional factors. An outline of the interview guide was sent in advance to the interviewees, to enhance the preparedness of the interviewees, which increased the likelihood of more specifically answered questions.
15 with operators of social micro hubs. Interviews were held at the offices of the respective companies, or at the respective social micro hubs, and varied in length between half an hour and one hour and a half. Nine consumers were interviewed. These interviews had a duration of approximately five minutes per interview.
Finally, additional data, such as informal conversations, performance data, observations, and documentation including internet pages, and newspaper reports supplemented the interview data.
3.2 The Case Study
The social micro hub delivery system of ViaTim is the network investigated in this study. ViaTim is the firm operating a social micro hub network. Besides ViaTim, data is gathered at web shops using ViaTim’s network, Wehkamp and goedkooproken.com, and the freight carrier collaborating with ViaTim’s social micro hubs, DHL. Table 3.1 summarizes the interviews conducted, and the stakeholder perspective of all of the interviewees, as well as their title. ViaTim started in 2016, and since then has grown to 800 social micro hubs today, called ViaTim points. It is headquartered in Schiedam, The Netherlands. At the time of writing, it employed 15 people. ViaTim has a large focus on the social aspect of social micro hubs. It hopes to expand these points beyond a parcel hub, by offering additional services, such as bike repair, clothes repair, washing service and book borrowing services. By doing this, it aims to connect the neighborhood and create efficiency.
Wehkamp is one of the largest fashion e-commerce companies in the Netherlands, with a turnover in financial book year 2016/2017 of 570 million euros. Goedkooproken.nl is a small web shop selling cigarettes and cigars.
DHL is an international parcel delivery and mail service. DHL is a global company, operating in 220 countries around the globe. In the Netherlands, DHL is the second largest parcel delivery company (Gras, 2016).
16 ViaTim Freight Carrier Social Micro Hub Operator Location: Veenoord HO1 ViaTim Freight Carrier Social Micro Hub Operator Location: Veenoord HO2 ViaTim Freight Carrier Social Micro Hub Operator
Location: Assen HO3
ViaTim Freight Carrier Social Micro Hub Operator Location: Groningen HO4 ViaTim Freight Carrier Social Micro Hub Operator Location: Groningen HO5
Wehkamp Sender External
logistics manager
S1
Goedkooproken.nl Sender Owner S2
Not Applicable Consumer Consumer 9 Consumers
interviewed
C1 / C9
Table 3.1 – Interviewees, their stakeholder perspective and their title 3.3 Data analysis
After the interviews, recordings were transcribed within two days, to enhance the validity of the transcripts. Thereafter, interview transcripts were sent to the interviewees to validate the correct interpretation of the interviews. Next, interview data was analyzed, and a coding tree was created, see Table 3.2. To do so, interviews were coded, initially in a deductive manner, based on the design factors identified in Chapter 2. Subsequently, data was coded in a more open fashion to extract additional design factors and other information not identified in Chapter 2. As a next step, these 1st order codes were merged into 2nd order codes, by merging all similar codes under one code. Following, 2nd order codes were grouped together in one 3rd order code when codes were similar, but not the same. Coding was executed using the software tool “Atlas.TI”. Although results of this single-case study cannot be generalized, the results of this research give a deeper understanding of the phenomenon.
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3.4 Coding Tree
The coding tree has been established based on the conducted interviews and can be seen in Table 3.2. Second order factors in roman follow from deductive coding, factors in italics follow from open coding.
During the interviews, it became apparent that next to the design factors for the stakeholders identified in Chapter 2, design factors for the social micro hub itself are also present. Because of the logistical function the social micro hubs have, these factors are grouped under the freight carrier stakeholder. This does, however, mean that not all design factors in a stakeholder apply for all companies in that stakeholder group.
First, interviews were coded in a deductive manner, based on design factors as shown in Table 2.2.2. Subsequently, when coding in an open fashion, additional factors were identified for all stakeholders.
2nd order code 3rd order code Theme
Cost for senders Consolidation Efficiency Increase in scale
Time savings (DHL data) Process inefficiencies
Reducing the not-at-home problem
Reducing the not-at-home problem
Less delivery personnel needed
Reduction in capacity needed
Decrease in total driving distance
Better location Convenience Consumer experience Shorter waiting times
Greater ease of return Timeliness
Flexibility
Longer opening times Opening times Ambiguity towards the
opening times
18 Decrease in fraud
Potential increase in fraud Unfamiliarity
Cohesion Social Value Social Value
Need for social interaction Need for anonymity
Reliability Reliability of delivery network
Reliability
Decrease in CO2 emission CO2 emission Environmental effect
Decrease in noise levels Noise levels Traffic congestion Traffic
Quality consistency Quality of hub Social Micro Hub design considerations
White label Design social micro hub Maximum number of parcels
Improving image for sender Other aspects Other aspects Improving image for freight
carrier
Differentiation Customization Use of private space
Extension service points network
Facilities
Table 3.2 – Coding Tree
4. Findings
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4.1 Efficiency
The use of social micro hubs can increase the efficiency in the last mile. Efficiency is also the most used code in the coding process. All interviewees at least mentioned efficiency as an important driver for social micro hubs.
Cost for senders makes efficiency important for senders. For goedkooproken.nl (S2), this even was one of the primary reasons to select ViaTim as a sending partner, as becomes clear from the following quote: “Besides, the shipping tariffs at [competitor] increased. By doing everything with ViaTim, we did not have to increase our shipping costs”. For the interviewee from Wehkamp costs seem to be a slightly less important factor for choosing ViaTim, but he also argues that delivery costs must be sufficiently low to be able to offer free delivery to the customer. According to the interviewees, efficiency is mainly affected by the increase in scale, and reducing the not-at-home problem.
Increase in scale is an important driver for increased efficiency. This becomes apparent from a quote of FC1: “It is much more efficient for us to deliver ten parcels to one address than ten parcels to ten addresses. So, in the short term, there is simply a lot of gain in the network.” Although this is considered to be true for last mile solutions in general, FC2 argues that social micro hubs enable this increase in scale better than most other last mile solutions.
Time savings are shown in data provided by DHL. The data shows the efficiency potential of social micro hubs. The dataset consisted of a sample delivery area, in which the average time per stop with traditional delivery is 2 minutes and 21 seconds. The average number of parcels on an afternoon in the sample was 25. The time needed at a service point generally is 7 minutes plus 25 seconds per parcel. This means that for this sample area, if all parcels would be delivered to the ViaTim point, the required time would be 17 minutes, compared to 54 minutes for traditional delivery, saving 68% in time in the residential area. Because parcels are delivered to the social micro hub, parcels still need to be transported to the consumer. Parcels can either be delivered or picked up by the consumer. Although this can potentially be just as time-consuming as traditional delivery, this is executed by either the social micro hub operator or the consumer, which is cheaper than delivery by a deliverer. However, it is worth noting that delivery from the ViaTim point to the consumer is currently only taking place in pilot-form, which is inconsistent with the vision of the company that ViaTim has.
20 to the hubs is not sufficiently streamlined. There are different vans for delivery streams and return streams, so every social micro hub has to be visited twice, once for the delivery of parcels, and once to pick up return parcels. Furthermore, since parcels to social hubs (and other service points) and consumers are in different delivery streams, multiple vans have to go through the street on a single day. This might be efficient for DHL but is not efficient for the amount of logistical movements in the urban area, nor for the ViaTim point operator.
Reducing the not-at-home problem is another important driver for increased efficiency. Since all parcels can be delivered to the ViaTim point, the number of second-attempt deliveries is reduced, as mentioned by multiple interviewees (S1, FC1, and FC2). Every day, DHL has approximately 20.000 parcels that go out for delivery for a second time. It has been said by four interviewees that ViaTim does not have this problem, because parcels are delivered to a social micro hub operator, who agrees to be home at the delivery time.
Less delivery personnel are needed because of the efficiency gain achieved when using social micro hubs. This especially means that less delivery personnel are needed, which is beneficial for freight carriers, because of the shortage of delivery personnel. The shortage on personnel has been confirmed by three interviewees (S1, FC1, FC2).
A decrease in total driving distance can also be achieved with the use of social micro hubs. According to S1, FC1, and FC2, less vehicle kilometers are necessary to deliver all parcels to the ViaTim points compared to traditional delivery, where parcels are delivered to the consumer’s front door. Because of this, fewer delivery vehicles would be necessary.
4.2 Consumer experience
Customer experience is affected by the following factors: convenience, opening times and safety. The use of social micro hubs makes it possible for the freight carrier and the sender to improve the customer experience. The importance of customer satisfaction and customer loyalty for senders is stressed by FC1, who states that when customer satisfaction and customer loyalty would be low, he expects that Wehkamp will stop using ViaTim points.
Convenience
21 Better location improves convenience as stated by one the interviewees: “I am positive about it [a social micro hub]. I think you should get your parcels as close to the customer as possible.” - S1. Most interviewees agree that it is important to deliver the parcel as close to the consumer as possible (S1, FC1, HO1). When using social micro hubs, parcels can get delivered to either the front door of the consumer, or to the social micro hub, where the consumer can pick up the parcel. According to the founder of ViaTim (FC1), ViaTim tries to open ViaTim points at locations where there are no or few retail service points, so that the ViaTim point is the closest location to the consumer. According to both S1 and FC2, this is the preferred strategy, because competition between service points would be avoided.
Shorter waiting times compared to a retail service point also add to convenience, according to FC1: “There will not be a queue of [] five other people, because a social micro hub just serves a lot fewer households. In contrast, a package point can traditionally handle seventy or eighty packages per day.” However, observations at one of the visited social micro hubs showed that many people come around the same time, and that waiting times thus also occur at social micro hubs.
Greater ease of return also adds to the convenience of a social micro hub. According to FC1, because a consumer does not have to bring the parcel to a drop-off point, but instead the ViaTim operator can come to pick it up, returning the parcel is less work and thus more convenient for the consumer. This is illustrated by the following quote from FC1: “So imagine, you buy clothes online, you have tried that clothing, and you think well nine shirts tried on, I want to keep one, so eight have to go back. We know that the moment you have to walk to a retail service point, that you will probably do that the next weekend, and if you cannot do it, then you’ll do it the weekend after. The return process usually takes between five and twelve days, before your clothes even arrive at that return process. With ViaTim we can pick up the package at your home, so you have tried it, you send a WhatsApp, "you have to pick up my package", and we [the social micro hub operator] come to you.” This is beneficial for the consumer, who has to put in less effort to return the parcel. Furthermore, this also advantageous for senders because the seller can resell the item faster. It is argued that in case of seasonal items, this is extra important for the seller, since a longer return time might mean the season for that item has finished by the time the item returns.
22 two movies in that time”. Using ViaTim, consumers can potentially get a more specific time window from the ViaTim point operator, by directly communicating with the ViaTim point operator.
Flexibility in when and where consumers want to receive the parcel could be possible with the use of ViaTim. According to the founder of ViaTim, a goal is to have communication between the consumer and the ViaTim point operator to discuss when and where the customer wants his or her parcel delivered, summarized by “your parcel at your moment”. However, as previously discussed, this is currently not (yet) the case.
The delivery pattern of returning consumers was also analyzed, as can be seen in Appendix B. However, due to the limited data available in this dataset, no conclusions can be made based on this data.
Opening times
The longer opening times of social micro hubs compared to retail service points are considered an important aspect of social micro hubs by all interviewees. Because many retail service points are only opened during daytime working hours, the consumer often fails to pick up the parcel when the consumer gets home from work. Since every ViaTim point has to be open at least between 16:00 and 21:00, the consumer can pick up the parcel or get it delivered when he or she gets home from work. This was also confirmed by two of the interviewed consumers (C5, C8) who were working during the day and picked up the parcel after work.
23 picked up or will be delivered. This is expressed as follows by FC2: “So they [customers] do not see if that point is open tomorrow or not and that is the problem of the web shops in the checkout. How did they explain that, or not, and if you order this you will see if can pick it up tomorrow or not? [...] Ideally, also from DHL you would say: if you are a social point then you are open six or seven days, and not three. Because that is just very difficult to explain to your customer. But yes, if someone says' I want to do it [open a ViaTim point], but not six days ... It is a difficult choice.” Both FC2 and S1 indicate a preference for uniformity in social micro hubs’ opening times.
Safety
Perceived safety issues were the reason of interviewed potential users of ViaTim points not to use ViaTim. Multiple consumer (C1, C3, and C4) indicated that they would not feel comfortable if their parcel would be in hands of someone they do not know, and that they would feel more comfortable if the delivery process would be handled by traditional delivery or retail service points. According to FC1, this is mainly because it is a new concept and consumers are unfamiliar with it.
A decrease in fraud compared to other last mile solutions is expected by the founder of ViaTim (FC1), because of the relation that ViaTim point holders have with the ones they would be stealing from. A potential increase in fraud is expected by S1 and FC2. However, they do think this threat is more likely to come from organized crime opening social micro hubs than from private individuals.
Unfamiliarity from the consumer towards the concept in general is illustrated by the following quotes: “It is somewhat unknown to customers, so customers do not know exactly what it is.” - FC1 and: “I think that if you ask a customer, that they do not know at all what it is. If I say ViaTim or social micro hub, then they don’t know what I’m talking about” - S1 When interviewing consumers in the same street where a ViaTim point was located, none of the interviewees (C1, C2, C3, and C4) knew that there was a ViaTim point in their street, or what it was.
4.3 Social value
24 Cohesion in the neighborhood could be increased by using social micro hubs, according to FC1. The main reason for this would be that people would talk to each other more frequently, increasing social activity. According to the founder of ViaTim (FC1), this is also one of the goals of ViaTim: creating convenience and efficiency by connecting people.
Need for social interaction was however also doubted as a need for all individuals, as illustrated by the following quote: “It can be someone you do not like at all. It can be that you do not want social cohesion in your neighborhood at all.” - S1. Moreover, some of the social micro hub operators (HO1, HO3, and HO4) indicated that they did not know who regularly used the point, so it is questionable to what extent the social cohesion in the neighborhood is already growing. Another social micro hub operator (HO5) said that many consumers used her ViaTim point, and she thus did not know the individuals.
Need for anonymity at pick up can be important to individual consumers. However, the opinions are divided on the impact this has on consumers. Some interviewees (S1 and FC2) think that this would be a reason for consumers not to use ViaTim, because of the potential sensitivity of online orders. Other interviewees (S2, FC1) think that this is not an issue, due to the disguised packaging used by many senders in those industries.
4.4 Reliability
25
4.5 Environmental effects
A decrease in CO2 emissions, a decrease in noise levels and traffic congestion are grouped
together as the 3rd order code “environment”, since most interviewees named them together as
environmental aspects.
A decrease in CO2 emission produced by vans might be possible if social micro hubs are used
due to the reduced driving distance. However, according to several interviewees, the way consumers travel to the ViaTim point, or the way the ViaTim operator delivers the packages, is going to be relevant to the real impact on the environment. If packages are delivered to or picked up by the consumer by car, then the environmental gain is going to be significantly less than if all parcels are delivered and picked up by foot or bicycle.
A decrease in noise level is can also be achieved, albeit very minimally, according to FC1 and FC2.
Traffic congestion can reduce due to decreased driving distances for delivery vans, according to three of the interviewees (S2, FC1, FC2). On the other hand, some of the interviewees are more skeptical, and point to the fact that delivery vans constitute only a small fraction of traffic in a city. Moreover, they are also skeptical about the traffic situation around the social micro hub, because it is unknown how consumers will come to pick up the parcel. If many people come by car, this could severely worsen the traffic situation in that area, since the infrastructure is not designed for that purpose.
4.6 Design
Design of the social micro hub consists of the following three factors which will be explained in the following section: quality consistency, white label, and maximum number of parcels. According to S1, it is important to have a consistent concept, as illustrated by the following quote: “So that is one of the things that I still find a big question mark, what the minimum requirements of such a point should be. Because if there is a different proposition in every street, you will not get it explained.”
26 – FC2. This also illustrates that there is a role for ViaTim in establishing quality assurance protocols, and again stresses the importance of uniformity among social micro hubs.
White label or branded ViaTim points is an important question for the design of ViaTim points Currently, all ViaTim points are only used for shipments from DHL and branded as DHL service points. Two of the interviewees (S1, FC2) questioned the sustainability of this concept and see a white label social micro hub as a more future-proof concept.
The maximum number of parcels per ViaTim point are a discussion point for the interviewees. While some of the social micro hub operators prefer as many parcels as possible (HO3), another social micro hub operator (H5) wants a maximum of ten parcels per evening, because otherwise it is too much work. For DHL, the number of parcels is only related to the demand in the area.
4.7 Other aspects
The following are factors that have been identified in the coding process, but not yet discussed: improving image, differentiation, customization, use of private space, extension service points network, and facilities.
Improving image can be achieved by both the sender and the freight carrier. S1 says that the use of social micro hubs can help create a social and environmentally friendly image. However, S2 says that the use of social micro hubs has a very limited effect on image. Both FC1, FC2, and S1 think that the image of the freight carrier can become more innovative with social micro hubs.
Differentiation through the use of social micro hubs is difficult to achieve. The interviewee from Wehkamp (S1) argued that customers will probably not choose for Wehkamp, just for its delivery method, but more for brand experience, price and personal taste.
Customization is identified because of potential parcel customization at the social micro hub, for example wrapping parcels in gift wrap, which is easier to do locally than at a large e-commerce retailer, according to S1.
Use of private space enables the concept to grow quickly, because the local government has less influence over it, according to FC1 and FC2.
27 Facilities at a service point can potentially be wider than at other last mile solutions. The founder of ViaTim (FC1) wants the ViaTim points to be more than merely a distribution hub. Potential services would be the intake of recyclable products and waste, or the central lending of items (e.g. drills).
5. Discussion
In this chapter, the findings of Chapter 4 will be set in context of literature. Firstly, factors found relevant to social micro hubs are compared to the literature on other last mile solutions. Secondly, factors relevant to social micro hubs that are not found in literature on other last mile solutions will be discussed.
5.1 Non-unique factors
The following design factors found relevant for other last mile solutions are also relevant to social micro hubs, and will be discussed in this chapter: cost, increasing scale, total driving distance, customer satisfaction, customer loyalty, use of public space, location, timeliness, social value, anonymity, CO2 emission, noise levels, traffic congestions, and differentiating.
This means that these variables are applicable for last mile solutions in general and are not specifically linked to social micro hubs.
The only factor identified in Chapter 2 that is not proven to be relevant to social micro hubs is “range of vehicles”. This is probably due to the specific character of this factor to other last mile solutions, such as electric vehicles (Pelletier et al., 2016).
28 happen in the same way as with social micro hubs. Cost of pickup and delivery can also be reduced by using social micro hubs. According to Wasner and Zäpfel (2004), pickup and delivery costs occur between pickup or delivery at the customer and the hub. By making consumers execute the last step in the delivery process for a small compensation, lower than a paid employee usually receives, costs for pickup and delivery are relatively low. Furthermore, delivery from the hub to the customer can be executed without the need for motorized vehicles, due to the proximity of social micro hubs to consumers, which reduces cost even further. Traditionally, costs of hubs are dependent on e.g. their number and size (Wasner and Zäpfel, 2004). However, since expenses such as rent, and utilities are paid by the social micro hub owner, operating costs for the hubs are virtually non-existing.
Increasing scale can lead to further efficiency gains, because more parcels get delivered to a single destination. Secondly, the deliverer spends less time searching for addresses. Thirdly, the not-at-home problem is less relevant because the social micro hub operator is at home when the freight carrier delivers the parcels. Thus, a social micro hub has potential to counter the three biggest inefficiencies discussed by Gevaers (2011).
Total driving distance traveled by vehicles delivering parcels is comparable to other last mile solution where scale is increased due to delivering more parcels to one location. Examples of such solutions are lockers and retail service points (Weltevreden, 2008).
Customer satisfaction and customer loyalty can be influenced by the choice for social micro hubs, which is in line with the findings of Thirumalai and Sinha (2004). Customer satisfaction and customer loyalty can be improved more with social micro hubs than with other last mile solutions, because the seller indicates that customer satisfaction and customer loyalty are expected to improve through the use of social micro hubs, even though other last mile solutions are already used by the seller.
The use of public space is in line with Weltevreden (2008), who argues that the rapid expansion of a last mile solution might be encumbered when this takes place on public ground, due to the necessity of permits from local governments. Social micro hubs are able to grow more quickly, because of the use of private space, as opposed to lockers on public space.
29 Timeliness at social micro hubs can be higher compared to other last mile solutions such as traditional delivery, because the consumer can either communicate with the social micro hub operator about the delivery time or can pick it up when he or she prefers. When picking up the parcel, timeliness is comparable to lockers and retail service points, because the consumer determines when he or she picks up the parcel (Deutsch and Golany, 2018; Weltevreden, 2008). Social value is more important for social micro hubs than for other last mile concepts. Social value can be of added value for a last mile delivery solution, which is argued by Vakulenko et al. (2018). It is also shown that there is a difference in need for social interaction among individuals (Vakulenko et al., 2018). However, social value is only a small aspect of many last mile solutions, where social value is an important driver for social micro hubs, as findings of this research suggest.
Anonymity is less apparent at social micro hubs than at other last mile solutions, such as lockers (Weltevreden, 2008), because of the interaction between the consumer and the social micro hub operator. Consumers who prefer anonymity at pickup can thus better use other last mile solutions such as lockers, that do offer anonymity (Weltevreden, 2008).
CO2 emission can be reduced using social micro hubs, and is an important driver for last mile
solutions, in line with previous literature. Similarly, noise levels can be decreased with the use of social micro hubs. However, this seems to be less important than is the case with other last mile solutions, such as cargo bikes and electric vehicles, as described by Pelletier et al. (2016) and Anderluh et al. (2017).
Traffic congestion can be reduced with the use of social micro hub in a similar way as other last mile solutions that implement the consolidation of parcels, such as lockers (Deutsch and Golany, 2018) and retail service points (Weltevreden, 2008).
Differentiation is hard for senders to achieve using social micro hubs, although this was expected based on Joerss et al. (2016), who found that choice of last mile logistics can improve differentiation from competitors.
5.2 Unique factors
30 perceived safety. This indicates that these design factors are uniquely related to the concept of social micro hubs and are therefore new in academic literature.
Ambiguity towards opening times is considered an important issue for social micro hubs. The need for consistent opening hours and days to decrease customer ambiguity is not described in literature about other last mile solutions, possibly because it is not applicable to most other last mile delivery solutions. However, Johnson et al. (2008) show that consumer ambiguity does negatively influence customer satisfaction in a self-service technology setting. Parcel delivery to a front door occurs most days of the week (Ducret and Delaître, 2013), and in case delivery is not seven days per week, it is often a fixed day on which delivery does not happen. Pick up points and lockers also have fixed opening times and days.
One of the underlying reasons for this ambiguity is that the system does not allow for lateral transshipments. Lateral transshipments are shipments from one base to another (Lee, 1987), within a single echelon (Banerjee et al., 2003). In the case of social micro hubs, all social micro hubs would be in a single, lower echelon. For social micro hubs, this would mean that parcels that are not picked up or delivered on a certain day can be shipped to another social micro hub for delivery or pick up the next day if the first hub is closed the next day. Lateral transshipments can lead to substantial service level increases (Hoadley and Heyman, 1977; Karmarkar and Patel, 1977; Tagaras, 1989). However, this does increase transport costs and complexity of the system. Furthermore, it is a requirement to have multiple hubs in close proximity to each other, to limit traveling distance for consumers to the social micro hub and to limit transport time for the lateral transshipments. With fewer locations in the lower echelon, service levels generally tend to deteriorate (Banerjee et al., 2003).
31 Image has a different effect on stakeholders in social micro hub context than is described in literature. The findings showed that image is mainly relevant to the freight carrier. However, from literature, it was expected that the choice of last mile delivery methods would mainly influence the sender (Joerss et al., 2016). The corporate image of a firm relates to the image of a firm in the eye of its stakeholders (Amores-Salvad et al., 2014; Van Riel and Fombrun, 2007). Although a lot of literature is available on the relation between corporate image and green initiatives, such as from Amores-Salvas et al. (2014), there is still very limited literature available on the influence of green initiatives in logistics on corporate image.
Customization at social micro hubs can be less expensive than at a large e-commerce retailer. Findings showed that it would be cheaper for the sender to postpone parcel customization until the parcel is at the social micro hub. Lee (1987) argues that postponement of customization can reduce cost if an agile workforce is created, which is in line with the findings of this study. Extension of the service points network can be achieved by opening social micro hubs. Findings of this research show that the use of social micro hubs was a way to quickly increase the number of service points. According to Visser et al. (2014), the use of retail service points in general can be advantageous because of potential consolidation of parcels.
Administrative control on social micro hubs is less than on other last mile solutions. Findings show that administrative control on social micro hubs currently is minimal. Literature suggests that local governments prefer to dictate the organization of a neighborhood and to plan retail areas. One of the reasons for this is to adjust infrastructure for different types of urban areas (Guy, 1998). In The Netherlands, the government has a strong control on retail locations (Guy, 1998). For lockers, administrative control is also larger, as permits are required before lockers can be placed (Weltevreden, 2008).
Flexibility of time and location for the consumer can be offered in a different way than at other last mile solutions because of improved communication to the consumer. Findings show that flexibility is high because of the communication between the social micro hub operator and the consumer, a feature often absent from other last mile solutions. The use of communication can benefit logistical processes (Pokharel, 1999), improving flexibility.
32 Perceived safety for consumers can be countered by measures such as the light level and openness of space. Findings show that some customers might have issues regarding the safety they perceive of a social micro hub compared to other last mile solutions, such as retail service points. Although no literature is available on how to increase perceived safety of consumers in a parcel delivery setting, Loewen et al. (1993) show that perceived safety can be influenced by the availability of light at a location and the openness of space. Both could be included as requirements for social micro hubs to increase perceived safety for consumers.
6. Conclusion
This study has examined the role of social micro hubs in the last mile from a supply chain perspective. Social micro hubs are a new last mile concept in The Netherlands, and are service points for the receiving, sending and delivery of parcels. The goal of this research was to uncover the role this last mile solution can play in parcel delivery. While many other last mile solutions have been studied extensively, there is a lack of research on social micro hubs. This study lays the groundworks for future studies on social micro hubs.
Using a case study, the Dutch social micro hub startup ViaTim has been researched in their logistical context. Eighteen people have been interviewed: two from a freight carrier perspective, two from a sender perspective, five social micro hub operators and nine customers. Furthermore, qualitative data was added to the dataset to calculate potential efficiency gains. Design factors for social micro hubs were extracted from the interviews. These design factors were subsequently used to define the role of social micro hubs.
This research has shown that social micro hubs can have an added value in the supply chain, by increasing both efficiency and customer experience in the last mile. By adding an additional link in the last mile supply chain, efficient linehaul transport increases, and delivery costs decrease. Moreover, environmental effects of last mile delivery can be decreased, and social cohesion in neighborhoods can potentially be improved. The use of social micro hubs can thus improve the last mile delivery process, beneficial for all stakeholders involved.
33 The implementation of social micro hubs comes with some complexities too. Customer ambiguity towards opening times is a problem that is unique for social micro hubs. The lack of consistent opening hours leads to ambiguity for the customer, who has to be informed proactively about when and where he or she can pick up the parcel. A potential solution would be the use of lateral transshipments, in which parcels would be shipped from one social micro hub to another. However, this would impact the costs and complexity of the system.
The reliability and quality of the individual social micro hubs is also considered to be an important factor. The findings of this study show that it is considered harder to achieve consistent quality and reliability with many individuals operating a last mile solution, than with a professional organization, e.g. a retail chain.
An interesting aspect of social micro hubs is the reverse logistics. Reverse logistics are an important cost for e-commerce retailers. The longer the return period for a seasonal item, the higher the devaluation of this product, effectively making the e-commerce retailer losing on the product. Social micro hubs can potentially reduce the return time of parcels due to increased convenience and an increased number of time windows in which the customer can return the parcel to the social micro hub.
To reach the full potential of social micro hubs, delivery from the social micro hub to the consumers should be offered. With delivery, location of delivery can improve, and flexibility can improve, allowing the sender and freight carrier to offer a more complete last mile solution to the consumer, while still benefiting from efficiency gains.
6.1 Directions for future research
The main limitation of this study is the lack of generalizability of the findings. Due to the exploratory nature of this study, only one social micro hub concept in a specific context has been studied. Further research should focus on testing the findings from this research in a broader context, i.e. with different social micro hub concepts in different settings of the parcel delivery market.
35
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