MANUFACTURER
AND OMNI-CHANNEL
RETAILERS LAST
MILE DELIVERY IN
SWEDEN
PAPER WITHIN Sustainable Supply Chain Management AUTHORS: Jakobsson, Christoffer & Nourparvar, Aein TUTOR: Andreas Risberg
JÖNKÖPING May 2021
A study on the last mile delivery settings of
manufacturers and omni-channel retailers compared
with the customer’s demand.
Mailing address: Visiting address: Telephone:
Box 1026 Gjuterigatan 5 036-10 10 00
551 11 Jönköping
Acknowledgement
We would like to take the opportunity to give a special thank you to our supervisor Andreas Risberg for helping and guiding us throughout this research paper. He has always been available for meetings, answering e-mails and giving valuable feedback. But also, by challenging us in our research area. Without Risberg this research paper would never be possible. Furthermore, we would like to thank our study colleagues for giving us valuable feedback and inputs during our meetings. To friends, family, and colleagues in our class, thank you for your support and encouragement during this project.
Jakobsson, Christoffer
Nourparvar, Aein
This exam work has been carried out at the School of Engineering in Jönköping in the subject area Sustainable Supply Chain Management of the three-year Bachelor of Science in Engineering program. The authors take full responsibility for the opinions, conclusions, and findings presented.
Examiner: Jan Weiss
Supervisor: Andreas Risberg Scope: 15 credits (first cycle) Date: 2021-05-26
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Abstract
Purpose: The purpose of the study is to explore manufacturer and omni-channel
retailers last mile delivery in Sweden. Then to recognize the main customer demand and compare it with the last mile delivery setting of manufacturer and omni-channel retailers last mile delivery.
Method: To reach the purpose of the study, quantitative approach study and
literature review have been conducted. Where the data has been collected through online search observation, document and record analysis and web survey. The companies (omni-channel retailers and manufacturers) that was chosen based on mix of micro, small, medium, and large size enterprise. The quantitative data was analyzed with the theoretical framework to reach the results. Then a web-survey was carried out in order to collect data about the customer demand on LMD.
Findings: The findings display that omni-channel companies performed better in a lot
of the last mile delivery settings such as velocity, free returns, offers more than one delivery mode, time slot, work with more than one delivery company. While manufacturers and omni-channel performed the same when it comes to last mile delivery mode. The only last mile delivery setting that manufacturer performed better in where the delivery prices towards customers. While overall the omni-channels performed better according to the customer demand than the manufacturers. But both types of companies did not perform well at all when it comes to environmentally sustainable deliveries. There was a high customer demand for freedom to choose last mile delivery mode, free delivery, free returns, and last environmentally sustainable deliveries.
Implications: The theoretical implications are towards the academic research about
manufacturers last mile delivery practice in Sweden. Since it is one of the first large scale research for manufacturers e-commerce last mile delivery. It is also important to note that the framework developed in this research were evolved from existing
research Hübner et al. (2016) and Marchet et al. (2018). The managerial implications are that manufacturers and omni-channels can benchmark themselves within the developed framework in order for them to make relevant decisions within their last mile delivery practice to be able to meet the customer demand.
Limitations: This research only focus on manufacturers e-commerce and
omni-channel retailers operating in the Swedish market, it does not cover pure e-tailers. The study has not explored any fulfillment strategies or warehouse locations.
Key words: Last mile delivery, omni-channel retailer, manufacturer, e-commerce,
Summary
2
Abbreviations
3PL: Third Party Logistic Provider APL: Automated Parcel Locker B2B: Business to Business B2C: Business to Consumer BSEK: Billion Swedish Krona C&C: Click and Collect C2C: Consumer to Consumer GHG: Greenhouse Gas HD: Home Delivery LMD: Last Mile Delivery
LMSNs: Last Mile Supply Networks OC: Omni-Channel
SCB: Statistics Sweden, Central Bureau of Statistics SEK: Swedish krona
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Table of contents
1 INTRODUCTION ... 1
1.1BACKGROUND ... 1
1.2PROBLEM STATEMENT ... 2
1.3PURPOSE AND RESEARCH QUESTIONS ... 3
1.4SCOPE AND DELIMITATIONS ... 3
2 METHODS ... 5
2.1RESEARCH DESIGN ... 5
2.2RESEARCH PROCESS ... 6
2.3DATA COLLECTION ... 7
2.3.1 Literature review ... 7
2.3.2 Online search observation ... 8
2.3.3 Web survey ... 9
2.3.4 Documents and records analysis ... 11
2.4DATA ANALYSIS ... 11
2.4DATA QUALITY ... 12
3 THEORETICAL FRAMEWORK ... 14
3.1E-COMMERCE AND LAST MILE DELIVERY ... 14
3.2COMPANY TYPES ... 14
3.2.1 Omni-channel retailer e-commerce ... 15
3.2.2 Manufacturer e-commerce ... 15
3.3LAST MILE DELIVERY SETTINGS ... 17
3.4CUSTOMER DEMAND ON LMD SETTINGS ... 21
3.5SUSTAINABILITY ... 22
3.6DEVELOPED LAST MILE DELIVERY SETTINGS FRAMEWORK ... 24
4 FINDINGS ... 26
4.1MANUFACTURERS LMD SETTINGS ... 26
4.1.1 Manufacturer last mile delivery mode and offers more than one delivery mode ... 27
Contents
4
4.1.3 Manufacturers price for customers and free delivery if order is over certain value
... 27
4.1.4 Manufacturer free returns alternative, number of transportation companies offered, and environmental sustainability work ... 28
4.2OMNI-CHANNEL LMD SETTINGS ... 30
4.2.1 Omni-Channel last mile delivery mode and offers more than one delivery mode . 30 4.2.2 Omni-channel delivery time ... 31
4.2.3 Omni-Channel price for customers and free delivery if order is over a certain value ... 31
4.2.4 Omni-Channel free returns alternative, number of transportation companies offered, and environmental sustainability work. ... 33
4.3CUSTOMER DEMAND ON LMD ... 33
4.3.1 The most important LMD settings according to the customers ... 33
4.3.2 Customer demand on LMD mode ... 34
4.3.2 Customer demand of LMD prices ... 35
4.3.3 Customer – manufacturer or omni-channel? ... 35
4.3.4 Customer demand of sustainability ... 35
4.3.5 Customer on why they choose to order from e-commerce. ... 36
5 ANALYSIS AND DISSCUSSION ... 37
5.1SIMILARITIES AND DIFFERENCES BETWEEN MANUFACTURER AND OMNI-CHANNEL RETAILER LMD SETTING (RQ1 AND RQ2) ... 37
5.1.1 Last mile delivery mode and offers more than one delivery mode ... 38
5.1.2 Delivery time ... 38
5.1.3 Price for customers and free delivery if over is over a certain value ... 39
5.1.4 Free returns alternative, number of transportation companies offered, and environmental sustainability work... 40
5.2 CUSTOMER REQUIREMENTS ON LAST MILE DELIVERY COMPARED TO THE MANUFACTURER AND OMNI-CHANNEL LMD(RQ3) ... 41
5.2.1 Meets the demand and somewhat meets the demand ... 41
5.2.2 Does not meet the demand ... 42
5.2.3 LMD opportunities ... 44
6
CONCLUSION ... 46
6.1CONCLUSION ... 46
6.2THEORETICAL IMPLICATIONS ... 47
6.3MANAGERIAL IMPLICATIONS ... 47
5
REFERENCES ... 49
APPENDICES ... 56
APPENDIX 1:LAST MILE DELIVERY SETTINGS EXPLORED. ... 57
APPENDIX 2:WEB-SURVEY QUESTIONS ... 59
List of Figures
Figure 1: Swedish e-commerce turnover graph (E-barometern, 2021: E-barometern 2015) ... 1Figure 2: Structure of the report ... 4
Figure 3: Research design the figure ... 5
Figure 4: Visualization of the research process and how it links together, own interpretation of Lekvall and Wahlbin, (2001) ... 6
Figure 5: Age segmentation of the web survey respondents ... 10
Figure 6: Gender segmentation of the web survey respondents ... 10
Figure 7: last time the web survey respondents ordered through e-commerce. ... 11
Figure 8: Supply chain structures (Pu et al., 2020). ... 16
Figure 9: Echelon structured logistics (Bowersox et al., 2013) and simplified logistics structure for manufacturers operating in e-commerce. ... 17
Figure 10: LMD cost per unit (Gevaers et al, 2014). ... 19
Figure 11: The companies within the parcel market in Sweden, sized on market share... 20
Figure 12: Important characteristics of LMD according to customer survey (E-barometern, 2021) ... 22
Figure 13: if end-customers were willing to wait 1-2 more days for the last mile delivery if it was more sustainable and companies were asked what they believe their end-customer thought. (E-barometern, 2020) ... 23
Figure 14: LMD Settings framework developed through a literature review. The highlighted red parts are our contribution to the framework and white is from Marchet et al. (2018) and Hübner et al. (2016) ... 24
Figure 15: Manufacturer LMD framework ... 26
Figure 16: Manufacturers free return alternative ... 29
Figure 17: Omni-channel framework ... 30
Figure 18: omni-channel´s that offers any type of free return. ... 33
Figure 19: The most important LMD settings for the customers. ... 34
Figure 20: Customer mode on last order and demand for LMD mode. ... 34
Figure 21: What customers are willing to pay for LMD. ... 35
Figure 22: If customers would rather buy from a manufacturer instead of an Omni-channel retailer. ... 35
Figure 23: Customer demand on sustainability ... 36
Figure 24: Summarized both manufacturer and omni-channel LMD settings framework from the findings. ... 37
Contents
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List of Tables
Table 1: Search method used for finding literature ... 8
Table 2: Company size definition (Eurostat, 2016). ... 9
Table 3: The manufacturers in the data collection. ... 9
Table 4: the omni-channel retailers collected. ... 11
Table 5: Manufacturer LMD velocity ... 27
Table 6: Manufacturer HD prices ... 28
Table 7: Manufacturer solitary C&C prices ... 28
Table 8: Omni-channel retailers’ velocity ... 31
Table 9: Omni-Channel HD prices. ... 31
Table 10: Omni-Channel C&C - Attached (including in-store) prices. ... 32
Table 11: Omni-Channel - Solitary C&C ... 32
Table 12: If the manufacturers and Omni-channel Retailers meet the customer demand. ... 41
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1 INTRODUCTION
The first chapter will consist of a background of e-commerce growth, the last mile delivery modes for manufacturer e-commerce, and omni-channel retailers. After the background of the research subject, the purpose and the research questions will be stated. Besides, the delimitations will be stated and defined then, at last, the outline of the research will be presented.
1.1 Background
Companies have started to use different channels to get their products to the end customer. The fastest-growing channel is e-commerce. It has gone from something new to an established way of buying and selling goods and services (Qin et al., 2014). The Fortune 500 list, which is a list that ranks the biggest companies in the USA. In 2020, the first and second companies are Walmart and Amazon (Fortune 500, 2021) both companies have a big e-commerce presence. In Sweden, 2003 the total turnover of e-commerce in Sweden was 4,9 BSEK and fast-forward to 2020 the total revenue was 122 BSEK (E-barometern, 2015; E-barometern, 2021) which is an increase of approximately 2489.80%. This means that e-commerce has been growing at a rapid speed over the last two decades.
Figure 1: Swedish e-commerce turnover graph (E-barometern, 2021: E-barometern
2015)
The COVID-19 pandemic has also factored into the rapid expansion of e-commerce. In a time when people have been forced to socially distance and abide by restrictions, e-commerce has become a safe way to buy goods without jeopardizing health and safety measures (OECD, 2020). With an increasing demand for e-commerce, there have been both opportunities and adversities. But first what is the definition of
e-Introduction
2
commerce? Mourya and Gupta, (2015) describe e-commerce as a developing model of processes of buying and selling goods through the internet. E-commerce is
straightforward; it means that someone is buying something over the internet without physical contact with a store or a salesperson. There are different types of companies that are present in e-commerce with some examples being multi-channel retailers, omni-channel retailers, e-commerce retailers, and manufacturers.
Due to the extreme growth of e-commerce, manufacturers have also entered the Business to Customer Market (B2C) with e-commerce instead of just selling Business to Business (B2B). Therefore, it is important to explore the manufacturers’
commerce last mile delivery settings to compare. Manufacturers entering the e-commerce market is an evolving trend. For example, earlier this year Volvo cars presented that by 2030 they will only sell new cars through their own e-commerce (Olander, 2021). In e-commerce, there is a lot of activity that can be challenging for companies in contrast to offline markets, such as last mile delivery, as well as their logistical activity. The activity from the customer order until it is in the customer’s possession includes the last mile delivery. Researchers have referred the last mile delivery to be one of the hardest things to manage within e-commerce and that the logistical cost of last mile delivery accounts for 30% of the total logistics cost in the supply chain. (Wang et al., 2014). Furthermore, in other studies by Mangiaracina et al. (2019), last mile delivery adds a lot of complex processes for that company. On the other hand, according to Lim et al. (2018) when customers order from e-commerce, they value the last mile delivery to work since it gives the customers comfort and convenience.
When it comes to omni-channel retailers e-commerce there is a lot more established research compared to manufacturer e-commerce, that explore their last mile delivery practice. Some examples are Marchet et al. (2018) and Hübner et al. (2016), both these papers have developed omni-channel frameworks for their last mile delivery settings. But on the other hand, to our knowledge there are no frameworks for manufacturer e-commerce. Which means that there is a gap in the research of manufacturer e-commerce, last mile delivery.
1.2 Problem statement
More and more, manufacturers are establishing direct to customer selling through e-commerce, while continuing to sell to retailers (B2B) (Pan, 2019). Moreover, due to the growing e-commerce of manufacturers direct selling to end-customers many manufacturers have a potential with the customers (Endo & Kincade, 2005). In line with the growth of e-commerce in the two last decades and within e-commerce, the last mile delivery is one of the most complex processes, and the last mile delivery is a very costly, wasteful, polluting, and ineffective process (Gevaers et al., 2009). Last mile delivery is a complex process for all companies within e-commerce.
To our knowledge there is no current research of manufacturers’ e-commerce last mile delivery setting in Sweden, which means that it is a gap in this research area. manufacturers’ have traditionally developed and produced their products and sold them to retailers and then the retailers have sold them to the end-customer. However, since manufacturers have their own e-commerce, it is important to see how their last mile delivery settings are configurated and compare them to omni-channel last mile
3
delivery settings. Since a lot of last mile delivery research has been conducted on omni-channels and they are considered to be big actors within e-commerce. To benchmark, manufacturers and omni-channel retailers last mile delivery with the actual demand will give the best result to evaluate both company’s performance. This research will fill the gap on manufacturers last mile delivery settings by comparing it with omni-channel retailers last mile delivery settings and then to benchmark with the actual customer demand.
1.3 Purpose and research questions
The purpose of the study is to is to explore manufacturers and omni-channel retailers last mile delivery in Sweden. As a result, the aim of the research is to recognize the main aspects of the last mile delivery that enable to meet their customer requirements.
➢ Research Question 1: What is the manufacturers e-commerce and
omni-channels e-commerce last-mile delivery settings in Sweden?
Then the frameworks are used to compare manufacturers’ and omni-channel retailers’ LMD setting in order to answer RQ2 which is stated below.
➢ Research Question 2: What are the similarities and differences between the
last mile delivery settings for omni-channel commerce and manufacturer- e-commerce?
Then by exploring the customer demand of the LMD settings with the frameworks developed, the reality can be compared with the customer demand to see if the companies perform in line with the customer requirements. At last, the main purpose of this thesis it to explore the LMD settings of manufacturer e-commerce and omni-channel retailers. In order to investigate gaps and opportunities within their last mile delivery compared to the customer demand.
➢ Research Question 3: How well does the manufacturer last mile delivery and
omni-channel last mile delivery meet the customer requirements on last mile delivery, and what are the opportunities for the manufacturers and omni-channel retailers when it comes to last mile delivery?
1.4 Scope and delimitations
This study will only focus on the manufacturer e-commerce and omni-channel retailers on the Swedish market, pure e-tailers will not be considered. Furthermore, attended, and unattended home delivery will be referred to as one type of delivery mode and that will be called home delivery (HD). This also applies to, attached C&C and in-store C&C, both of those will be referred to as attached C&C. This study will
Introduction
4
cover all company sizes micro, small, medium, large. The research will not be observing the practice of the reverse logistics although will cover the cost of the returns for the customers. In extent the research will not go in-depth about the configurations of companies’ fulfillment strategies and warehouse locations.
1.5 Outline
Here is an outline description of the report:
Chapter 1: The chapter describes the background of the study; it describes the
problem statement that why this study is conducted. The purpose of the study, the research questions, scope and delimitations and outline of the research have been highlighted.
Chapter 2: This chapter will cover the research methodology, research design, and
our data collection, and the research process.
Chapter 3: This chapter will include the theoretical framework of this research, with
information about e-commerce, manufacturer, omni-channel retailer, last mile delivery settings, customer demand on last mile delivery and sustainability we will cover the theoretical framework that supports last mile delivery in omni-channel retailer and manufacturer and sustainability within last mile delivery.
Chapter 4: In this chapter the findings of the data collection will be presented: first
the last mile delivery framework for manufacturers and then the framework for omni-channels. Then the customer demand will be displayed.
Chapter 5: This chapter will analyze the data collected with the literature review.
First out is the contrast and comparison of the manufacturer and omni-channel
frameworks. Then it is followed by the customer demand analysis together in compare with the frameworks.
Chapter 6: This chapter will include the conclusion of the research and present future
research suggestions.
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2 METHODS
The following chapter discusses the underlying methodology for the thesis. It starts with defining the research design, then leading to the research process. Thereafter the next part is followed by the explanation of data collection and analysis. Lastly, the quality of the research is discussed.
2.1 Research design
In order to address the research topic, we have decided to conduct an exploratory research. We decided to use a fixed research design which means that there is a clear purpose and steps are mapped in a chronological order to answer our research
questions. Research design means, “The focus in research design must be the production of the knowledge required to achieve that objective ‘what’.” (Tobi & Kampen, 2018, p. 1212). To answer our research questions, we have decided to use multiple process steps with four different methods. The methods are literature review, online search observation, document and record analysis and a web survey. First, we will conduct a literature review. Andreini & Bettinelli (2017) describes it as, literature reviews are performed since it looks at previous data to create new knowledge and questions.
Therefore, a literature review is needed to understand current research and to develop our own last mile delivery settings framework to answer RQ1 and in extent to be able to answer our RQ2 and R3. The framework will evolve and developed in the literature review from two current research papers with developed frameworks by Marchet et al. (2018) and Hübner et al. (2016). Furthermore, the rest of literature review will cover more last mile delivery settings and cover a large part of the customer demand on last mile delivery.
Moreover, an exploratory research design fits well to our research, since an
exploratory research are usually carried out if previous research is outdated or if there is little exiting research on that topic (Hair et al., 2020). By develop a framework, we will explore both the manufacturers and omni-channels retailers to get a better understanding of last mile delivery settings and compare it with the customer’s demand. Our fixed exploratory research design is visualized in figure 3.
Methods
6
There are three different types of reasoning when writing a research paper, deductive, inductive, and abductive reasoning. The first of these methods, deductive reasoning, utilizes current theories and logic to rationalize raw data (Kennedy & Flick, 2018). Inductive reasoning is opposite of deductive, as it relies on examining empirical evidence and identifying patterns in order to reach conclusions (Kennedy & Flick, 2018). Finally, abductive reasoning, the reasoning we are relying on for this thesis, is founded in the creation of new logic by examining outlying or surprising factors that prior knowledge cannot be applied to (Kennedy & Flick, 2018). Since manufacturer e-commerce last mile delivery practices B2C is an evolving concept, the research about this is limited. On the other hand, similar studies have been conducted on other e-commerce last mile practices. Therefore, abductive reasoning is suitable for this study. Furthermore, when researchers utilize abductive reasoning, they realize that their conclusions could be temporary and are subject to change. This process of thinking fosters "powerful iterative processes between data collection and analysis, and between data and theory" (Kennedy & Flick, 2018, p 17).
2.2 Research process
The study was undertaken in three main processes: planning report, collecting data, and data analysis. Within the first phase, we had an introductory meeting with the supervisor to create awareness on the nature of the research. In the second phase, we discussed different data collection methods that will help us understand and interpret data, helping to create a framework for the LMD settings of manufacturers and omni-channels e-commerce. Finally, the last phase involved the analysis of the collected data from different methods that we used which are, literature review, web survey, online search observation and document and record analysis in order to extract relevant insights that facilitated addressing the research questions. Figure 4, we display the process of our research and how the processes are connected.
Figure 4: Visualization of the research process and how it links together, own
7
2.3 Data collection
In this research we have chosen four different methods for data collection. Data collection is a crucial task in the research process. Choosing the proper data collection method is depends on the research questions (Hair et al., 2020). The first method we used was a literature review on current established literature within our topic. The second, was an online search observation of companies’ websites. The third data collection is a web survey, where we have sent out a survey to e-commerce
customers. The fourth data collection method was a document and record analysis of previously collected data.
2.3.1 Literature review
First data collection is a literature review on current research that will give us a great foundation to explore the topic but also to develop a framework. “A review of previously conducted research on similar topics is often helpful in moving from pure observation toward some working discovery or idea.” (Hair et al., 2020, p. 42). With the literature review, we will be able to contextualize our other data, as it allows us to interpret a large amount of information with relation to our topic (Bell & Waters., 2014)
In this part, textbooks, literature, scientific articles, and journals are included. According to Easterby-Smith et al. (2015), a literature review will create balance between the knowledge and chosen topic. Jönköping University’s own search engine Primo is efficient and developed tool that has a wide collection of various databases, and it is according to us the best tool to have a good start for searching literature review. By using different ways of search and using advanced search with developing in keywords and search terms found more relevant literature related to research topics. ProQuest was the main database that we used in this research. As categorized in table 3, we use some keywords for our literature search. Easterby-Smith et al. (2015) notes that peer-reviewed articles are considered to be critical sources across many academic disciplines, therefore making them a key part of our research study. Hence, we focus on peer-reviewed research to make connections between research questions and the purpose of our study. After finding the relevant article, we read the abstract and review that article and put it in our share research article sheets. In the final steps we did a full text review. The full text of the article was reviewed and used in order to get relevant information for the study topic.
Methods
8
Key words Search terms Nr. hits Abstract read
regarding “peer review” articles. Used Last mile delivery setting
“Last mile delivery” 1739 34 10
Last mile delivery in manufacturers
“Last mile delivery” AND “Manufacturers” 37 12 6 Last mile delivery in omni-channel retailer
“Last mile delivery” AND “Retailer”
42 23 4
Customer demand on last
mile delivery
“Last mile delivery” AND “Customer demand” 6 3 3 Sustainable mode on last mile delivery
“Last mile delivery” AND
“Sustainability”
68 23 7
Table 1: Search method used for finding literature
2.3.2 Online search observation
The second data collection is an online search observation form the manufacturers’ websites. The internet has made it easy for people to get a lot of information at once; one online search can get thousands of hits. This means that we need to explore what information we needed, to search for as well as which available sources we want to utilize for collecting proper information (Hair et al., 2020). In the online observation we have collected data from 50 manufacturers that sell B2C through e-commerce. Since we wanted to get data from all kinds of company sizes and from multiple different industries, we chose to do an online search observation of over 50
manufacturer e-commerce websites. We focused on manufacturers that sell directly to customers, not via retailers and wholesalers; also, they should have delivery to
Sweden. By conducting the online observation of secondary data, we will get a lot of information about a lot of companies. Since the actual data we are collecting is quantitative, no further data needed to fulfill the aim of the first research question. In order to segment the companies have we used a definition from Eurostat Glossary: enterprise size to determine the segmentation of the companies. According to the Eurostat there are some different criteria that can be used to determine the size of the company “e.g., number of persons employed, employees, balance sheet total,
investments” (Eurostat, 2016). The most common way to determine the size is, however, the number of persons employed (Eurostat, 2016). That is the way we will determine the size of the companies in this research. There are four different
segmentations defined by Eurostat and those are: large, medium, small, and micro. The definition of each segment is displayed in table 1 and then followed by the manufacturer companies’ size within this research in table 2.
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Company category Staff headcount
Large Enterprises 250+
Medium-Sized Enterprises 50-249
Small Enterprises 10-49
Micro Enterprises 0-9
Table 2: Company size definition (Eurostat, 2016).
Table 2 displays the company sizes of the data collected in the online search
observation; we have tried to cover all types of company sizes from micro to large.
COMPANY SIZE (EU) standard Number of companies % Large 19 38% Medium 8 16% Small 6 12% Micro 17 34% TOTAL: 50 100%
Table 3: The manufacturers in the data collection.
2.3.3 Web survey
The third data collection is web survey, which is a useful and widely used method when the goal is to answer research questions that needs a lot of primary data to fulfill the purpose (Ruel, 2019). This method of data collection with aid our research, since it grants the collected data for customer demands of last mile delivery process more reliability. We have decided to create a web survey, and we gathered our samples by surveying people who have ordered online in the last year. We tried to include many age and gender demographics as possible. Since according to Cowels & Nelson, (2015) it is important for sample the people in accordance with people you are interested in to get the best sample size to give proper result. Since we are first exploring how the LMD settings are for manufacturers and omni-channel
e-commerce. Before conducting a survey, it is important to see how others have asked questions and what kind of questions that should be included in the web survey (Cowles & Nelson, 2015). Furthermore, the literature review helped us to identify the key questions to the web-survey.
By surveying different people from Sweden, we attempt to discover various answers on the customer demand of last mile delivery in Sweden and examining how different variables affect the answers. The web survey consists of eleven questions which are, (age, gender, last time order of ordering online, what delivery mode did you chose last time you ordered online, why did you order online instead of going to the store, which
Methods
10
delivery mode do you prefer, what is the most important for you when it comes to last mile delivery settings when ordering online, should companies be more transparent with their sustainable work when it comes to deliveries, what would you be willing to do for a more sustainable delivery, what do you think is an acceptable price for delivery? (SEK), if possible, would you rather buy direct from the manufacturer instead of a retailer). We posted the web survey in our LinkedIn and Facebook so that different people from different (backgrounds, educations, ages) can respond to. We mentioned two criteria for this web survey, which is that the responder should live in Sweden and have an experience of online shopping within the last year. In total, we got 105 respondents.
In the three figures below our sampling of the respondents are displayed in order to show who responded to the web-survey will add the validity of the survey. First the age segment is displayed, then the gender segment and last setting where that the customers had to have ordered through e-commerce within the last year.
Figure 5: Age segmentation of the web survey respondents
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Figure 7: last time the web survey respondents ordered through e-commerce.
2.3.4 Documents and records analysis
The fourth data collection will be documents and records analysis of quantitative data that was previously collected by an assistant professor, he has conducted the data collection of these 50 omni-channel retailers last mile delivery settings by conducting interviews and surveys. By being supplied with the omni-channel retailer data the extensive data collection will become much more effective in order to answer our research question. This data will be the foundation for our framework of omni-channel retailers and therefore a crucial part to answer our research questions. The sampling of the omni-channels was the same as the manufacturer display to have companies that are both large, medium, small micro.
COMPANY SIZE (EU) standard Number of companies % Large 20 40% Medium 10 20% Small 10 20% Micro 10 20% TOTAL: 50 100%
Table 4: the omni-channel retailers collected.
2.4 Data analysis
Quantitative research can also be exploratory, which is generally focus on different aspects that are included, find relationship, interpretation and characteristics of the study's topic that mention the new theory or new problems (Swanson & Holton, 2005). The data was collected through four different sources, online search
Methods
12
stages of data collection, the researcher was carefully evaluated and considered the data to determine its relevance and significance to research topic. In addition, a literature review was the first data collection which carried out in parallel with the other data collection method. The data collected from online search observation and document and record analysis were transcribed to Excel files by researchers in order to visualize and analyze data. One excels file consist of information about
manufacturer, another includes of answers from web survey, and the last one
contained data about omni-channel retailers. With this classification, researchers get accurate overview of data, and it helps to researchers to analyze and compare how manufacturer e-commerce and for omni-channel e-commerce apply last-mile delivery practice in Sweden.
In addition, during the literature review various databases and sources containing information about the last mile delivery from manufacturers and omni-retailer were analyzed. The findings were analyzed and compared to the theoretical framework to determine the most credible source and use as a basis for the research questions. A web survey was conducted to gain more knowledge about the customer demands of last mile delivery in e-commerce. Together with the other findings from the data collection, it was analyzed to answer RQ3. After the web survey was conducted, the data was first checked for completeness and quality. We then transcribed the answer from the survey to an excel sheet in order to have a complete overview for analyzing the gathered data. All data from the web survey was analyzed without attribution of missing values.
Moreover, we analyzed the data from online search observation and document record analysis to get point for the first and second question research questions. Then for the third research question, web survey data was used to increase the validity and give more complete overviews for analyzing the data.
2.4 Data quality
As Lincoln and Guba (1985) mentioned, for the quantitative research, validity and reliability are more fitted as the research quality criteria. We have used Bernard (2000) definition of validity which is “the accuracy and trustworthiness of
instruments, data and findings in research” (p.46). The researchers believe that this study has high internal validity because the data has been collected within the different methods.
In order to ensure the reliability and validity of the data collected in the research, it was important to ensure appropriate data collection methods were used. Reliability is explained as the ability of a process to get the same results every time (Bell & Waters, 2014). The data was collected from companies’ websites and document and records analysis from the professor. Also, validity is more complex, it explains how the researcher designed the structure of the study to get trustworthy conclusion. (Bell & Waters, 2014). In order to ensure the data collection methods utilized in the research gather valid data, the researchers designed the web surveys. With comparing and matching different answers from conducted web survey, the authors gave more validity to the findings and extended the quality of data collected. Examining the
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answer form several aspects which are age, gender, level of education, location in our web survey gave more validity to our data.
However, to increase reliability of the study, the authors collected data that fitted more relevant to the research purpose. “Triangulation is the use of multiple sources of data, different research methods and/or more than one researcher to investigate the same phenomenon in a study” (Collis & Hussey, 2014, p.71). This can reduce bias different process which are included data sources, methods, and investigators. Also applying multiple data collection methods helps the researcher to look the problems from various perspectives that investigate same result and providing they all attain the same conclusion. This process gives a more robust to the result and enhances the reliability and validity of the study (Denscombe, 2017). Moreover, the researchers believe that the study has high internal validity because the data has been collected within the different methods. As mentioned, “The internal validity of an information-gathering efforts is to extent which it actually (correctly) answers the questions it claims to answer using the data that were gathered” (Swanson & Holton, 2005, p. 77).
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3 THEORETICAL FRAMEWORK
This chapter will display the theoretical framework for this study, different research theories within last mile delivery, manufacturer commerce, omni-channel
e-commerce, last mile delivery settings, customers perspective, and sustainability. This will give the study a scientific foundation to identify the last mile delivery settings in order to develop a framework to answer RQ1 and RQ2. At the last, the theory within customer demand on last mile delivery will be identified in order to later help answer RQ3.
3.1 E-commerce and last mile delivery
E-commerce has revolutionized the buying and selling process, providing a digital means of exchanging information, products, and services. The digital phenomenon can greatly aid the globalization of markets, trade, and countries around the globe have taken note (Kamlesh et al., 2005). E-commerce has several types of categories, Business to Business (B2B), Business to Consumer and Consumer to Consumer (C2C). In this study we focus on B2C e-commerce which is defined as any business selling its product or services to consumers through the internet for their personal use (Kamlesh et al., 2005).
In e-commerce the last mile delivery can be described as the last step of the product flow to the end-customer (Bates et al., 2018). In e-commerce last mile delivery can be seen as the grand challenges especially in the business to customer e-commerce. LMD is the last step of the B2C regarding the delivery service whereby the product goes from the seller to the customers with different delivery modes such as home deliveries, solitary C&C and attached C&C (Devari et al., 2017).
LMD have different modes each modes have different features, and some can be effective while others are not. It is up to the logistics provider to offer the best
delivery option to the customer so that the customer satisfaction will increase by both considering the delivery time and then to saving money for the customer (Jomthong et al., 2018). Moreover, it is hard to manage LMD since it is usually small batches, high service cost (Feng et al., 2020). This makes it complex process for the companies while, yet it is very important. Last mile delivery is one of the important factors for e-commerce business. Therefore, many companies decided to create their own logistic network (Yu et al., 2017). In e-commerce business, the logistics section sometimes needs to cover all over the country or even all over the world. This can put full work and pressure on the logistics section of the companies. Therefore, some companies decided to outsource some part of their logistics services to third party logistic provider (3PL) companies. (Yu et al., 2017) Also to better meet the needs of seller and buyer, online sellers decide to extend their logistic network in last mile delivery service or 3PLs companies to send products to end customers (Jomthong et al., 2018).
3.2 Company types
The two company types that will be explored in the thesis are omni-channel retailer and manufacturer. By defining each of the two company types and brief discuss their different logistical structure.
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3.2.1 Omni-channel retailer e-commerce
Traditionally retailing has been brick and mortar stores but over the past several decades the retailing market has gone from physical store to multiple channels including the e-commerce. E-commerce has grown strong, and its significance has increased (Lim & Winkenbach, 2019).
Omni-channel is the new retailing strategy that came into the multi-channel retailing world, in order to provide a combined and integrated relation between consumers to generate a united experience regardless of the process. This new strategy complicates the logistics last mile process, as the customers pick their product from the store as the endpoint. Whereas now there are several endpoints, such as the physical stores,
solitary click and collect, or HD (Mohammad et al., 2020). There are three different types of retailers, non-store retailers, such as e-commerce, store-based retailers, such as supermarkets and hybrid retailers such as door-to-door sales, mobile trade etc. (Levy & Weitz, 2009). Retailers face some conflicts in their operations, and the modern last mile delivery is challenging process for them. (Lim & Winkenbach, 2019). Omni-channels gives the customers the shopping experience through multiple channels which makes the omni-channel retailers more accessible (Lim &
Winkenbach, 2019).
Last mile delivery is important to retailers since it is a complex process, it is the last step in the supply chain, and it is here the retailers, and the customers connects. Furthermore, it is a very expensive part of the supply chain. Due to this, retailers want to establish the most effective last mile supply networks (LMSNs) to meet the omni-channel retail challenges. LMSNs help with creating alignment in marketing and distribution channels to be successful in the e-commerce market. (Lim &
Winkenbach, 2019).
3.2.2 Manufacturer e-commerce
Manufacturers operating in e-commerce are responsible to make products and sell them to retailers or wholesalers in the supply chain. Also, they are responsible for both manufacturing and selling products to end customers. Manufacturers that produce and sell their products can engage in both the production and retail side of operations (Levy & Weitz, 2009). Furthermore, traditional e-commerce retailers are frightened about the entry of manufacturers selling directly to customers through e-commerce. The retailers think that over time manufacturers will take over a lot of the e-commerce retailers market share with their direct selling to customers. (Hu et al., 2020). Due to the current increase of e-commerce and the increased present of
manufacturers selling direct to consumers manufacturers can involve more segment of customer. When a manufacturer establishes an e-commerce with direct selling and continues to sell to retailers the supply chain structure looks like the figure 12 below (Pu et al., 2020).
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Figure 8: Supply chain structures (Pu et al., 2020).
An example of the supply chain structure above is NIKE, who has their established own e-commerce and in 2019, the direct e-commerce channel grew with 35%
compared to the brick and mortal stores sale which grew by 6% (Hu et al., 2020). It is not only in the clothing industry this is happening; the car manufacturer Volvo Cars has also established their own online channel. Volvo´s new e-commerce make is possible for customers to design their own car features direct to Volvo and when the order is confirmed they can choose where they want to pick it up (Allhorn., 2017). To further distinguish the differences between a Manufacturer and an omni-channel retailer the differences are presented in the table below. The first flow chart represents echelon structured logistics, this means that the product flows is already established and are stored at each node before continued shipment to the next. Which creates a straight flow from supplier to the end customer. (Bowersox et al, 2013). While on the other hand, the second flow chart represents a logistical structure where the
manufacturer both sell B2C and B2B, meaning that the company is both the producer of the goods but also has its own channel to reach the end customer. (Levy & Weitz, 2009). Sa seen in the flow chart below, the manufacturer and the retailer (omni-channel retailers) compete with the same products towards the same customers (Hu et al., 2020).
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Figure 9: Echelon structured logistics (Bowersox et al., 2013) and simplified logistics
structure for manufacturers operating in e-commerce.
3.3 Last mile delivery settings
To explore the Last mile delivery (LMD) settings of the manufacturer and omni-channel e-commerce the settings need to be defined. There are two previous research conducted on omni-channel last mile delivery first by Hübner et al. (2016) and then further developed by Marchet et al. (2018). Both of those researchers have created a LMD framework to group the LMD settings. The purpose of Hübner et al. (2016) were to develop a framework for omni-channel retailers grocery stores and to highlight the advantages and disadvantages of the LMD settings. This papers LMD framework were then further developed by Marchet et al. (2018) and their purpose were to explore the logistical settings of omni-channel retailers, and to detect the most common practice. Researchers have mostly been researching from a sales perspective. While Marchet et al. (2018) and Hübner et al. (2016) cover the logistical challenges with omni-channel e-commerce logistical practices.
Both the papers explore “four main logistics variables relating to the delivery service: delivery mode, velocity, time slot and slot price differentiation.” (Marchet et al., 2018, p. 446). These four logistics settings and the previous frameworks will be the
foundation for creating a new research framework by defining the settings. The first framework developed by Hübner et al. (2016) identifies four different variables. Which are delivery modes, delivery time (velocity and time slots), delivery area, and return. The second framework by Marchet et al. (2018) deems that the delivery services go under the strategic area, and that the logistics variables of that are; delivery modes, velocity, time slots, and slot price differentiation (Marchet et al., 2018).
Theoretical Framework
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The first setting is the LMD modes which is the type of delivery the company uses to get the order from the company to the customer it is important to define all the modes. Attended HD means that the receiver of the order needs to be present during the delivery (Hübner et al., 2016). The other type of HD is unattended which can be defined as the order will be delivered at home whether the receiver is there or not (Hübner et al., 2016). In addition, there are three types of click and collect alternatives described in both papers. The first is in-store C&C, which is when a customer goes to a store and picks up the order (Hübner et al., 2016). Attached C&C which is when the customer goes to a place attached to the company they order from and pick their order up there, it could be by a store, warehouse for example. In this research in-store C&C and attached C&C will be referred to attached C&C, due to their similarities in that the customer gets to a point that belongs to the seller to pick up the goods. Then last is solitary C&C, which means that the customer picks up the order at a designated pick-up location not attached to the e-commerce company (Hübner et al., 2016). When it comes to in-store C&C & attached C&C in this paper, will both be seen as one delivery mode due to the many similarities of them.
In Sweden, there are two different types of solitary C&C. The first is when the transportation company has an agreement with an entity so that the customer goes to that entity and the entity will hand over the goods to the customer. One example of this is the 3pl company Postnord. Postnord is one of the biggest last mile delivery providers in the Nordic countries that had a revenue of 37,7 Billion SEK and roughly 30 000 employees in 2018 (E-barometern, 2020). Postnord has about 1 600 pick-up points across Sweden which act as solitary C&C for companies that sell online. Their goal is to have the Solitary C&C at places where people go every day such as grocery stores and convenience stores. It should be noted that Postnord strives to have the Solitary C&C at those places so that people do not have to go out of their way when picking up packages ordered online from E-commerce (Postnord, 2021). The other type of Solitary C&C is when the package is delivered to an Automated Parcel Locker (APL). An APL is a type of locker that are used for packages handling in last mile delivery, it is and electronic locker which is opened by the customer with a code. APL´s are usually located close to the customers movement patterns (close to home, work, train station etc.). When choosing APL as the LMD mode the seller send the package to one of the lockers close to the customer’s needs. The locker is opened with the received code that he or she will be notified about (Rabe et al., 2021).
Another setting that the research has explored is delivery time which consists of velocity and time slot. The first sub section is velocity, which also can be referred to as delivery time means the time between the order has been sent until it is at the customer (Hübner et al, 2016). Velocity is a very visible and measurable setting both for customers and companies. Although, researchers do not think it is a key
differentiator when it comes to non-food retailers, since it is very costly for the company running in e-commerce. The different types of velocity presented is same day, next day and two or more days. If the velocity is same day, it means that the customer gets their product the same day the placed the order (Marchet et al., 2018). Delivery time is often driven by the customer demand, customers within e-commerce are demanding to get their goods within the time that the company says it will deliver meaning that the customer demands to get their orders within the agreed time
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The other setting is time slot, this means that the customers can decide the day or time when the delivery will occur. Some companies offer this while others do not, a time slot can be defined and undefined, if the time slot is defined the customers can chose the day and time when the order should be delivered (Marchet et al., 2018). Time slots can be a good tool to use for the companies since it helps the companies in “An
effective tactical way to obtain cost-effective delivery schedules is differentiated time slot pricing concerning delivery prices” (Klein et al, 2019, p. 236-237). At last, Marchet et al. (2018) has slot price differentiation in their framework, and it means that the company takes different fees depending on the picked time slot.
Customer satisfaction can also be affected by the pricing of the LMD for the customers. When a customer orders online he or she sometimes pays a fee for the delivery. Due to the increase in e-commerce more the customer within e-commerce have started to become demanding and the have started to see responsiveness as a service attribute (Ko et al., 2018). The cost of the LMD for the consumers and companies usually depends on the industry since companies have different sizes on their products, price of the product and the margin of the product assortment and how available the product are (Allhorn, 2016). According to researchers the LMD cost can vary depending on the population density, in an urban area with a population density of >1,500 inhabitants/km² the cost from LMD were about 2,75 EUR per unit and in areas with <50 inhabitants/km² the cost for LMD is 7,75 EUR per unit (Gevaers et al, 2014). According to SCB (Statistics Sweden, Central Bureau of Statistics) there are 290 municipalities in Sweden and 6 of them has population density >1,500
inhabits/km² (SCB). This needs to be considered when analysis the result since
Sweden is overall a very rural country compared to other European countries, Sweden has an average 25,5 inhabits/km². (SCB).
Figure 10: LMD cost per unit (Gevaers et al, 2014).
Some companies operating in e-commerce uses a technique when it comes to the customer price of delivery. This is called `free delivery over` and the technique is that if a customer orders exceed a certain price the company offers free last mile delivery to the customer. Usually does the companies offer free delivery if the customer order exceeds 500-599 SEK (Allhorn., 2016). Some companies offer free delivery on all
Theoretical Framework
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orders, although it is one of the costliest parts of the supply chain (Jomthong et al., 2018).
When it comes to returns, a study from Hjort and Lantz (2016) showed that there were no benefits for the company to offer free return. The positive aspects of free returns are far from the cost of the free return. Which does not make it long term profitable. Furthermore, customers who are repeated customers gives the company less profit if they offer free return. The only significant positive factor of free returns is that it can attract new customers to the company. Moreover, in a case study at a Swedish
retailer’s warehouse by Patel et al. (2021) the cost of managing the returns, labor and transportation costs are high and therefore free returns will hurt the company’s profit of the sold goods.
Another last mile delivery setting is that some companies partner with different parcel delivery companies. In a report from the Swedish Post and Telecom Authority (PTS) the parcel last mile market has been growing due to the rapid increase of e-commerce. In the same lines, the customers dictate the last mile delivery mode if they want to be able to decide when, how and to whom the goods should be delivered. There is one company within the LMD parcel industry that has 40% of the market turnover and that is Postnord. They are followed by UPS who has about 20% of the total parcel market. Then there are two companies that has 10% each: DHL and DB Schenker (Nysäter et al., 2020). Figure 11 is PTS´s parcel market share analysis displayed.
Figure 11: The companies within the parcel market in Sweden, sized on market share.
Further explanation of figure 15. a: TNT (1-5%), b: FedEx (1-5%), c: DSV (1-5%), d: Jetpak (1-5%), e: Best Transport (1-5%), f: Bring Parcel (1-5%). Other are companies with less than 1% of the market share individually. (Nysäter et al., 2020).
There is a tough competition between the delivery companies presented above. In extent there are also new competitors within the market that offers more personalized deliveries, and these companies has pushed the more established companies to
develop flexible delivery methods (Nysäter et al., 2020). While in some cases, there is a great challenge in Sweden when it comes to LMD to rural areas due to the travel time and less density of the population. Due to these challenges, deliveries to these
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places can be collaborated between companies in order to make it more efficient. For example, in some cases Postnord has greater advantages with home deliveries in rural areas, which mean that collaboration can be performed for those deliveries (Nysäter et al., 2020).
3.4 Customer demand on LMD settings
The diversity in delivery services and the quality of these services are important and main criteria of online customers when shopping online and have a direct impact on those who play a role in the success of e-commerce. Operations should work hard to offer the best delivery option according to the customer's situation, especially by improving the delivery time. New business models addressing demands of customers for a faster delivery are causing disruption in the last mile. (Joerss et al., 2016). Furthermore, due to growing of e-commerce, the business- oriented parcel-delivery market have grown impressively according to consumer preferences. large
Ecommerce actors and different startups have recognized the last mile delivery services as a key differentiator (Marchet et al., 2018). According to Mohammad et al. (2020), if a company understands their customers salient beliefs would help the company to perform better on predicting option-selection purpose and take strategic actions when it comes to deliveries and returns. Also, it will help the company to give the customers a better satisfaction.
Furthermore, delivery modes are important for both companies and customers since eight of ten (8/10) customers think it is important for them to be able to choose what kind of last mile delivery mode they want (E-barometern., 2020). In line with an increase in e-commerce, the customers are demanding even more flexibility when it comes to the delivery mode. Additionally, delivery time is an important LMD setting for the customers. According to researchers, the delivery time is a big part of
customer satisfaction, both in service, but also in the convenience sense since the customer order online since it gives convenience and it is also a big part of the service that the customers get (Hübner et al., 2016).
The LMD settings that go under the delivery time are velocity and time slot. Velocity means the speed that the order is delivered in, velocity depends on the industry and the product, it is also a highly visible service within the LMD. It can be defined as how fast the company gets the product from their possession to the customer (Marchet et al., 2018). As stated above, last mile delivery settings are important for the
customers, according to a recent survey 25% of all e-commerce customers in Sweden would like to have more than one delivery modes when buying online. In the same lines, more customers are demanding for freedom of choice when it comes to LMD modes 84% of the customers think it is important to be able to choose delivery mode in check out (E-barometern., 2021).
Last mile delivery can be a make or break for any company selling through e-commerce according to a study, “Logistics operations in urban areas, notably urban fulfillment and last mile delivery, tend to be the most expensive of the entire logistic process while being the most critical in shaping customer experience” (Kim et al., 2021, p. 1). Since customers are more demanding in terms of LMD modes, velocity and time slots, research shows that it is important for companies to build relationships with their customers. Researchers in e-commerce customer loyalty showed that the
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most significant factor for customer loyalty were competitive prices, but not only the prices. More important factors were good communication, good service levels and quality products. (Michałowska et al., 2015)
Figure 12: Important characteristics of LMD according to customer survey
(E-barometern, 2021)
According to E-barometern’s annual report 2019, there is an increasing demand from the end-customers that the last mile deliveries are sustainable this was shown in a survey where the end-customers were asked if they were willing to wait 1-2 more days for the delivery if it was more sustainable. 79% of the asked end-customers said yes, 13% said no, and 8% said doubtful/do not know. In the same lines, companies were asked what they believe if their customers were willing to wait 1-2 more days for the delivery if it is more sustainable. There were only 43% companies that answered yes and 20% said no, while 38% of the companies said doubtful/do not know.
3.5 Sustainability
From increasingly serving natural phenomena such as floods and severe storms, and human-made greenhouse gas (GHG) is said to be the main cause of global warming. GHG can be created through burning fossil fuels and deforestation, for example a way to decrease GHG output is to decrease fuel use and to use it more efficiently together. (Jomthong et al., 2018). Last mile delivery is a big contributor to pollution GHG since it is one of the most polluting part of the whole supply chain (Gevaers et al., 2011). The lion's share of GHG emissions comes from transportation, since fossil fuels are often used in place of more sustainable options. LMD freight traffic can increase congestions, carbon emissions and pollution. (Bates et al., 2018). With all this in mind, choosing a delivery mode that is most efficient can help reduce GHG
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emissions. As an example, customers select the nearest location for the post office to collect their product. (Jomthong et al., 2018).
According to a research the information the customers get from the companies when ordering from e-commerce is very little, there are no information to the customer about the environmental impact provided by the company they order from or the transportation company (Ignat & Chankov, 2020). That means that the customers are not aware of the environmental impact their order has. Furthermore, customers can often choose different LMD modes, and they can only take their decision established on economic factors, but in a research, they discovered that if the customer can base their decisions of last mile delivery with not only the time and cost but also the environmental and social impact, customers often picked the most sustainable one (Ignat & Chankov, 2020). This means that with transparency the customers make more sustainable choices. While some other research suggest that it is very hard for companies to both have sustainable LMD and appealing prices towards the customers (Buldeo et al, 2019).
Figure 13: if end-customers were willing to wait 1-2 more days for the last mile
delivery if it was more sustainable and companies were asked what they believe their end-customer thought. (E-barometern, 2020)
As the demand for sustainable solutions in all industries companies have now started to work more with sustainability, as shown in the last mile delivery 79% of the
customers were willing to wait longer for their deliveries if it was more sustainable (e-barometer, 2020). Sustainability can be defined as “to ensure that it meets the needs of the present without compromising the ability of future generations to meet their own needs.” (World Commission on Environment and Development. 1987, p. 16). When working with sustainability one of the most common concepts is called the triple bottom line (TBL), which consists of three different pillars which are: people, planet, profit. according to Grant et al, (2017), TBL means, firms need to maximize their shareholder wealth or creating economic value so long as they are adding value in social and environmental aspects to gain long-term natural environment security and living standards for all human beings with right working. This paper will only focus
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on the environmental aspects of the TBL. This paper will only focus on the environmental aspect of sustainability.
3.6 Developed last mile delivery settings framework
Through the literature review our research framework has evolved through the
findings of the current frameworks. The developed framework will be best suitable to answer our research question. First to explore the LMD settings of manufacturer and omni-channel retailers. With this framework, the RQ1 will be answered by presenting the last mile settings. The framework below has three highlighted parts this means that it directly coherent with the frameworks from Marchet et al. (2018) and Hübner et al. (2016). While the other settings were developed throughout the literature review of both the LMD settings and the customer demand.
Figure 14: LMD Settings framework developed through a literature review. The
highlighted red parts are our contribution to the framework and white is from Marchet et al. (2018) and Hübner et al. (2016)
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The framework consists of eight main LMD Settings that we have defined in our theoretical background. To break down the framework and how the settings have been chosen through a literature review we start with the first LMD setting. last mile
delivery mode, which has three different alternatives; HD (including attached and unattached), attached C&C (both in-store C&C and attached as in a
warehouse/distribution center), and solitary C&C. By exploring what types of LMD mode the companies are using the overall settings for the manufacturer and omni-channel retailers will be explored. In the same lines, the findings will give an estimation on what types of delivery mode these types of companies are using in Sweden.
The second LMD setting is if the company offers more than one LMD mode e.g., both HD and attached C&C. This setting is important since there is a demand from the customers that they can choose what type of delivery mode they want for the order. Since there is a high demand for freedom of choosing what type of LMD mode from the customers, almost 84% of the customers want to be able to choose the delivery mode (E-barometern, 2021). Therefore, it is important to see how this setting is executed by the two company types.
The third LMD setting that is explored is the delivery time, this consists of two sub-settings which are velocity and time slot. These are also two extremely important settings since 65% of the customers think it is important to get their delivery within three days (E-barometern, 2021). In the same lines, 79% of the customers think it is important to get a time slot when they order, it does not necessarily mean that they expect to have the freedom of choosing the time slot. However, the customers want to know when their order is being delivered (E-barometern, 2021). Additionally, the fourth setting explored in the framework is if the company has express delivery or if they do not have express delivery, this comes from the freedom of choice delivery mode, but also the freedom to choose the velocity of the order.
The fifth LMD setting is the price for the LMD, what are the delivery fees when ordering through e-commerce. This is crucial to find out how the respective company type is pricing their LMD. Furthermore, the framework also explores if there is a price difference depending on the model that the customer is choosing while ordering from e-commerce since 77% of the customers think it is important to get free delivery (E-barometern, 2021). Then by identifying the costs of the LMD both companies can be compared at LMD prices. In line with the pricing of the LMD, the sixth LMD setting that the framework explores is the returns, it is a key element in LMD settings since 77% of the customers think it is important that they are offered free returns on their products (E-barometern, 2021). The seventh LMD setting that the framework is exploring is if the manufacturer or the omni-channel e-commerce have one or more delivery companies handling the LMD. Then the eighth and last LMD setting is the environmental sustainability setting, which displays how many of the respectively companies offer an environmentally sustainable delivery option.
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4 FINDINGS
In this chapter the extensive data collection will be summarized. First the frameworks for manufacturers and the framework for omni-channels will be displayed and
summarized to answer give a foundation to answer RQ1 and RQ2. The data to the frameworks comes from the extensive online search observation and the data and record analysis. Next, the large web-survey data from the customers will be displayed to help answer RQ3.
4.1 Manufacturers LMD settings
In this section, the result of the online search observation of the 50 Manufacturer will be presented in the LMD settings framework to answers the RQ1 and give a
foundation for RQ2. In the table below the findings of the manufacturers are displayed.
