This chapter will provide reasoning for the conduction of the thesis. We will explain the philosophical background, research strategy and approach. Moreover, we explain and argue for the chosen methods. Finally, we state our considerations of the research quality and the research ethics.
As necessary for any research we made some considerations prior to this thesis to follow the most appropriate philosophy, including ontology and epistemology. The ontology is the assumption about the ‘form and nature of reality’, while epistemology covers the position of the ‘knower’ and ‘what can be known’ (Guba & Lincoln, 1994).
According to the definitions of Easterby-Smith (2015) our knowledge creation follows a constructionist epistemology based on the ontology of nominalism. Therefore, we assume that knowledge about CL networks is a human creation established through discourse among people. The creation and understanding of networks and innovations depend highly on the individual perspective of the actors. As a result, a common understanding or knowledge can only be achieved through discourse of those actors. Since there will never be total agreement among all actors in CL, the existence of multiple truths (Lee & Aslam, 2019; Yin, 2016) or no truth at all must be accepted (Easterby-Smith, 2015). The network reality and comprehensive attitude towards innovation is created by discussion and interaction between actors. Holliday (2016) acknowledges similar characteristics for what she phrases as postmodern constructivism. In her opinion reality is constructed and knowledge therefore created in discourse. Bell and Bryman (2011), who interpret constructionism as an ontology, add that meaning is not just created “through social interaction” (Bell & Bryman, 2011, p.22) but also constantly revised by social actors. Positivist or naturalist epistemologies are in our case neglected, as the aim is neither to establish nor test a single truth in form of a theory (Holliday, 2016; Yin, 2016). In addition, the complexity is part of the system, so simplified assumptions of more positivistic research may not cope with the problem (Easterby-Smith, 2015).
As Gergen and Gergen (2007) argue, constructionist scholars retrieve knowledge from the understanding of human relationships. From our understanding the actor networks represent inter-organizational and human relationships at the same time. The epistemology is further justified by the complexity of actor objectives shaping these networks through their interaction. The meaning of the network is constructed and revised by the perception of the involved actors.
The actors’ reality perspective on innovation in CL, their understanding of their own function and the CL networks contributions are highly relevant. Moreover, the flexibility of constructionism (Easterby-Smith, 2015) is supporting this research since the main objectives are revealed just in the research process and need to be treated as they come up. This is also supported by Holliday (2016), who points out the emergence of unexpected topics and intervention of the researcher throughout the research. This is a predetermined part of our research as e.g. newly identified actors need to be taken into account and integrated in the actors’ analysis. Furthermore, since we try to give meaning to the system of networks in CL, a rather strong constructionist approach is suitable (Easterby-Smith, 2015).
Therefore, we as researchers can also not claim an absolutely neutral position but are engaged in the researched subject to a certain degree (Holliday, 2016). As Yin (2016) supposes constructivism entails value bond research, which means that we as researchers influence the knowledge building by how we set up our research and interact with participants. Moreover, the research in CL is highly driven by the shared human interest in sustainable city environments and life quality. Therefore, we agree with how Holstein and Gubrium (2008, p.35) phrase it: “The truth is that we must live in the world if we would hope to understand it.”
Prior to any systematic approach we researched the field of CL actors to gain an overview of the topic. Thereof we formulated our two research questions.
Following our research philosophy, the research problem suggests a qualitative and exploratory approach (Creswell, 2002). According to the interpretation of Robson (2011) we follow an exploratory strategy, since the important variables and their impact were uncertain prior to the research. An explanatory strategy is not suitable as causal relationships between the factors can only be investigated if these factors could be determined beforehand.
A qualitative study allows us an in-depth investigation of the subject. Moreover, qualitative research offers the flexibility to steadily adjust the research according to the data gathered and context in the research process (Mason, 2017). So, we can include subtopics, which come up during the research and were not included in the initial setup (Lee & Aslam, 2019). Deeper exploration is possible as “topics and focuses emerge” (Holliday, 2016, p.6). This flexibility, which is also pointed out by Robson (2011) and Taylor and Bogdan (1998), is essential in our setting, since the objectives of the individual actors are initially uncertain. Thompson and Walker (1998) also support this argument as a qualitative study is appropriate if the impacting variables and their interrelation are unclear. This definitely applies if we interpret these variables as CL actors. In addition, we seek to explore a complex setting which simply cannot be expressed in numbers (Thompson & Walker, 1998). A quantitative research approach requesting a collection and analysis of numerical data is therefore not appropriate (Bell & Bryman, 2011).
Taylor and Bogdan (1998) state that qualitative research must be inductive as it develops understanding instead of assessing existing theory, which is congruent with our approach. We follow an inductive reasoning, as we increase the understanding of innovation in CL networks by conceptualizing (Merriam, 2002; Robson, 2011). We use the viewpoints of different actors to develop an understanding which leads to a more comprehensive understanding and the emergence of a framework. Thus, we “move from the particular to the [more] general” (Mantere & Ketokivi, 2013). Deduction as well as abduction as deriving reasoning from general theories or concepts are not suitable for the research approach (Mantere & Ketokivi, 2013; Yin, 2016).
In accordance to (Merriam, 2002), our research can be classified as a “Basic Interpretive Qualitative Study” (Merriam, 2002, p.6) with an inductive strategy and a descriptive outcome.
Research Design and Data Collection
Argument for the Design
To give a comprehensive understanding of the research questions we firstly defined the terms “CL” and “innovation” based on existing literature from prominent authors in the respective fields. To summarize the state of the art in research we conducted a systematic literature review on actors in innovative CL networks. In addition, we explained two existing theories which are most suitable as basis for our analysis.
As an attempt to answer our research question in an optimal way, we decided for an interview study. This is a suitable approach, as we want to investigate CL networks and innovation from the viewpoints of the interviewees who shape those networks (Taylor & Bogdan, 1998). In coherence with the constructionist approach the process of interviewing is part of the knowledge creation in a joint meaning making between interviewee and interviewer. As a result, every interviewee participating and also the researchers themselves are engaged in and responsible for the knowledge created (Holstein & Gubrium, 2008). By engaging with experts from the field we gain understanding of their individual perspective and meaning-making of their organization, their networks and their attitude towards innovation (Easterby-Smith, 2015). In addition, there are insights in the interviewees, their organizations self-understanding and their perception of other actors. Engaging with multiple actors additionally allows a more comprehensive meaning making about the interpretations of CL networks and innovation. Moreover, through the knowledge exchange in the interviews, we might also, to a very limited extent, shape the meaning making of the interviewees. In fact, from the constructionist viewpoint every interview can be interpreted as creating a new reality (Lee & Aslam, 2019).
In the given context the majority of the qualitative data needed can only be collected in interviews with experts of the individual organizations.
This exploratory approach fulfils our research purpose by giving us insight in the individual actors’ perspectives (Creswell, 2002) on innovation in CL networks, their contributions and objectives. Moreover, through an interview study we can identify additional actors from the contributions of the interviewees.
To establish a common understanding with the reader we defined the terms “city logistics” and “innovation” based on publications of prominent authors. It is essential to clarify our understanding due to the existence of multiple definitions of the used term and to assure the applicability of the concepts for this thesis.
This is followed by a systematic literature review with the aim to comprehensively (Yin, 2016) and critically (Saunders, Lewis, & Thornhill, 2012) cover the topic of actors in innovative CL networks. The systematic review supports this aim (Easterby-Smith, 2015). Moreover, it enables us to outline discrepancies and common ground among researchers as prerequisite to our own findings (Yin, 2016).
The key word search was conducted in the “Web of Science” with the search terms “((cit* OR urban* OR metropol*) AND logist*) AND (freigh* OR goods OR parcel* OR deliver* OR packag*) AND (networ* OR actor* OR player* OR partne*) AND (innovat* OR technol* OR sustaina* OR last mile OR last-mile)”.
The research fields where limited to “business”, “economics” and “transportation” to avoid purely technical and not actor-network related topics. The age of publications was limited to 15 years since the high pace of development in the field of CL requires some degree of currency. Since the investigated field is rather narrow and the investigation of actor networks is rather new, the search was not limited to high ranked journals. Moreover, not peer-reviewed articles and book chapters were also included if the authors expertise was verified by other publications in the field and they gave an impression of good research quality (Easterby-Smith, 2015; Saunders et al., 2012).
The search resulted in 120 articles from which we identified 62 as relevant. The high number of non-relevant articles is most likely due to the long and complex search term. For five relevant articles the scientific quality could not be sufficiently evaluated. One article could not be accessed. Through source tracking in the relevant articles two more publications were retrieved as relevant, which leads to a total number of 58 reviewed articles.
To frame our research findings, we evaluated different theories. Therefrom we identified and explained systems theory and network theory, which both comprehensively fit to our approach. Here the choice of literature was again primary towards the most prominent publications, but also for authors from the logistics or innovation field applying those theories on the respective topics. By combining the two theories we received a higher variety of considerations to answer our research questions. In fact, we were able to explain the interplay of actors in city logistics more comprehensively. In Figure 4 we illustrate the first emerged understanding of the connection of theories.
1.2. Problem Discussion
1.3. Purpose and Research Questions
2. Theoretical Background
2.1. City Logistics
2.2. Innovation in City Logistics
2.3. Actors and Networks in City Logistics
2.4. Guiding Theories
3. Research Methodology
3.1. Research Philosophy
3.2. Research Approach
3.3. Research Strategy
3.4. Research Design and Data Collection
3.5. Content analysis
3.6. Research Quality
3.7. Research Ethics
4. Empirical Findings
5.4. Emergent Framework
6.1. Consistency of Actor Groups
6.2. Evaluation of Actor Contributions
6.3. Network and System Relations
6.4. Current State of Innovation
7.1. Summary of Results and Contributions
7.3. Limitations and Future Research
8. Reference list
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Actors in innovative City Logistics Networks Individual Actors jointly forming City Logistics Networks and their Contribution towards Innovation