Research Methodology in Healthcare Logistics

Introduction

The preceding chapter presented the literature review, which covered the relevant studies pertaining to the improvement of healthcare logistics processes and provided the background and which is effective to progress in the study for better analysis and evaluation where the knowledge and understanding are important to gather more relevant data and analyse it efficiently. In this chapterthe research methodology of this study is explained. First, the philosophical position of this study is clarified. The three research questions presented in the introduction are then broken down into sub-questions, followed by an outline of the research objectives and the constructsinvestigated. Theory building within supply chain management and operations management is then discussed in relation to this thesis. A justification and description of the case study,research questions and research design (a mixed method research strategy) follows. The approach for data collection and analysis are presented, followed by an account of how quality of research is ensured. Finally, the nature of scientific contributions and their practical implications are explained.

The Research Philosophy

The philosophy adopted in this study is critical realism, which was first developed by British philosopher Roy Bhaskar inA Realist Theory of Science(1975). Critical realism was evaluated and expanded by Rutzou and Steinmetz (2018), who described itas representingrealistontology and a relativist epistemology. Theyreferredto ontology asa theory of being(i.e. what is real) and epistemology as a theory of knowledge (i.e. what is knowledge and what can be known and understood). In this particular study, ontology is the theories of supply chain management and operational management and on the other hand, epistemology is the knowledge and concept of the researcher related to the supply chain management which are effective to analyse this study and evaluate it fir better understanding and fulfilling the research aim. They also argued that in critical realism, reality is independent of human thought—in other words; it exists regardless of what is known (Rutzou and Steinmetz 2018). According to Bhaskar (2008) and Wynn Jr. and Williams (2012), it also has a stratified ontology consisting of three domains of reality: the empirical domain, the actual domain and the real domain.Of these domains, the real encompasses generative mechanisms while the actual comprises events caused by generative mechanisms in the real domain;both of these domains exist independently of the observer(Shields 2018). The empirical domain consists of events which the observer experiences; events occurring in the actual domain may or may not be observed by observers, and may be understood in different ways by observers (Bhaskar 2008).Bhaskar(2008) also argued that causal relationships are not necessarily observable and may only be the effect of an observed generative mechanism.However, from a critical realist point of view, causal relationshipsarecontext-specific.Context affects generative mechanisms and is an important part of understanding how they work (Archer 2012). According to Archer (2012), critical realism is inherently transcendental realist and assumes that the world is socially constructed.According to Bhaskar (2008) and Wynn Jr. and Williams (2012), critical realism seeks explanations rather than predictions because social systems cannot be contained and causes cannot be isolated, as is done in laboratory experiments. It is therefore possible to know what reality is, albeit people are unlikely to understand the whole truth(Easton 2010). Reality therefore exists, but knowledge is relative and theory-dependent (Aastrup and Halldórsson 2008; Bhaskar 2008). Working from a critical realist point of view, Aastrup and Halldórsson (2008) justified the use of case studies in logistics research as a means of reaching the necessary causal depth to reveal the real domain of logistics and uncover generative mechanisms.Case studies include causal powers and effects of intentions of agents, e.g. individuals, firms or organisational units. They also argued that case studies should be justified based not only on the capacity of a complementary or exploratory role but of a primary role in generating knowledge. The realist view is compatible with case study research done by Yin (2014) andAastrup and Halldórsson (2008). Easton (2010) argued that critical realism not only justifies the use of case studies but also guides how to conduct case research,as a case study is a research method particularly suited to critical realism which enables the investigation of clearly bounded and complex phenomena.

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This research investigates the complex phenomenon of improving healthcare logistics processes:The entities/objects characterising the investigated phenomenon and the factors impacting the improvement decision are identified and data collected to establish plausible causal mechanisms.Two types of generative mechanisms and events are investigated: the identified impact factors as a generative mechanism with the decision to implement changes to improve healthcare logistics processes as the event, and possible interventions as generative mechanism and the consequence of improved healthcare logistics processes as event. Easton (2010), referring to critical realism, argued that explanations are interpretivist in character and a researcher’s understanding of his or her subject’s understanding must be included in any report of that research. These understandings are assessedin the case study descriptions and data analysis.Retroduction, also called abductive reasoning, is a key epistemological process recognised by critical realists.In this study, the iterative process of abduction comprised the coding and re-coding of the data and the revisiting of sites (Voss el al., 2016). Easton (2010) emphasised that, the quality of an explanation should be assessed andit must be determined whether an explanation is ‘good’ or ‘acceptable’, and moreover a ‘judgmental rationalitymust also be applied in evaluatingthe existing arguments to reach a reasonable judgement of a reality. On the other hand, Voss el al. (2016) explained that, critical realist research is an iterative process and improves over time. Furthermore, the same study by Voss el al. (2016) was conducted in several iterations where as inductive approach is typically used for theory building, whereas an abductive approach is better suited to theory testing and the refinement of mature theories. In this case the case studies provide an in-depth understanding of specific incidents. The context of a case, the underlying mechanisms which generate a certain outcome and the observed outcomes may be observed as regularities within and across cases (Bryman 2012).Identifying the generative mechanisms is the aim and objective of this research. The use of mixed methods in this study is based on critical realism, as the use of multiple methods and data sources enables a deeper understanding of causality (Wynn Jr. and Williams 2012). Critical realism is also particularly compatible with the fields of supply chain management (SCM) and operations management (OM) due to its focus on empirical data and causality; it was chosen for this studybecause the focus of this research is on understanding the causalities of complex systems within SCM and OM (Rotaru et al. 2014).

The Research Aim and Research Questions

The research questions are closely related to the aim of the research and the problem statement, which was presented in the introduction.The research aim of this study was formulated as described below.

The Research Aim

The aim of this research is to provide theoretically and empirically based evidence for improving healthcare logistics processes to both expand the knowledge base of healthcare logistics and provide a decision tool for managers to improve healthcare logistics processes. The feasibility of a research question, and consequently the research method, depends on the maturity of the research field:Exploratory and descriptive research is suitable for a nascent research field, while explanatory and prescriptive research is suitable for a more mature research field (Åhlström, 2016). As the literature review revealed, the field of healthcare logistics research is relatively new, making this field a developing one which is neither nascent nor mature. The healthcare logistics research field is thus situated between nascent theory, which is a theory in early stage of development, and intermediate theory, which is between the two extremes of nascent and mature theory;it is close to being an intermediate theory, as illustrated in Figure (Åhlström, 2016).The existing literature therefore provides a foundation on which to build future research, albeit a narrow one.

The maturity of the healthcare logistics research field

The maturity of the research field is reflected in the primaryresearch question (RQ) posed in this thesis, presented below:

RQ: How can private nursing homes in the United Kingdom innovate their healthcare logistics settings to reduce costs and improve the quality of the process design and performance?

Despite the healthcare logistics research field being somewhat new, it has developed beyond the nascent stage and is approaching the intermediate stage, where more explanatory and prescriptive research is necessary. The RQ is therefore somewhat explanatory and prescriptive, as it is a ‘how’ question. To answer this RQ, four types of intervention, which were identified in the literature review, were investigated: 1) BPM, i.e. changes to process steps; 2) logistics and SCM interventions; 3) technological interventions; and 4) organisational interventions. The improvement of logistics processes is reflected in the RQ in terms of the ‘needs and preferences of private nursing homes’. This specific formulation of the RQ was chosen to reflect the fact that different private nursing homes may have different strategies, focus areas, political environments and social structures, and consequently their needs and preferences differ. As mentioned in Chapter 1, the costs and quality of service are major concerns in the healthcare industry and motivated this study. The cost and quality concerns involved in improving healthcare logistics processes are investigated in this study in terms of improving the efficiency and effectiveness of processes. Efficiency is input-oriented and concerns the economic use of resources, whereas effectiveness is output-oriented and concerned with achieving goals (Mentzer and Konrad 2011). Neely et al. (2015) put itsimply, stating that efficiency is ‘doing things right’ and effectiveness is ‘doing the right thing’. Thus the cost aspect is reflected in efficiency and the quality aspect is reflected in effectiveness, which in turn reflect performance (Neely et al., 2015; Mentzer and Konrad 2011). The RQ can be broken down into three partsandfurther underlying the research objectives, as follows:

Q1: What are the challenges and complexity of the various elements of the healthcare logistic processes?

1.1 What are the challenges specific to healthcare logistics processes?

1.2 Which interventions can private nursing homes implement to improve healthcare logistics processes?

1.3 Which benefits can be identified for interventions and approaches for improving healthcare logistics processes?

Q2: How can the identified impact factors be used to assess and innovate the healthcare logistics systems?

2.1 Which factors impact the design of healthcare logistics processes?

2.2 How do impact factors affect the design of healthcare logistics processes?

Q3: What is the impact of innovation on the design and performance of a process after implementation?

3.1 How can the identified impact factors be used to measure and benchmark the performance of healthcare logistics processes?

3.2 How can healthcare logistics processes be assessed to ensure a solution which best fits the preferences of a private nursing home?

The RQ1 considers the question ‘how could something be improved?’ in terms of composite design elements; RQ2 addresses ‘why this an improvement?’, as determined by impact factors; and RQ3 asks‘how should it be improved?’ based on an assessment. This progression of RQ’s follows thenatural order of making an improvement decision. The descriptive nature of RQ1 and the explanatory nature of RQ2 fit well with the maturity of the field. RQ3 is more prescriptive and is enabled by the preceding descriptive and prescriptive RQs. Furthermore, the predictive claims of the ‘could” and ‘should’ questions make this research useful to managers (Wacker 1998). Figure illustrates the hierarchy of research questions and the link between the research questions addressed in this thesis.

The Research Objectives

The research objectives describe the actions taken to answer the research questions and how the research aim is achieved. The overall objective of the research conducted in this study is to provide theoretical and empirical evidence to determine how healthcare logistics processes can and should be improved. This objective can be broken down into the following actions undertaken to reach the overall research objective and answer the RQs:

Identify possible methods for assessing the design and performance of healthcare logistics processes after determining the theoretical area of research

Identify the most suitable common and best private nursing home practicesfor investigation;

Identify relevant processes for investigation the logistics system; and evaluate the case studies in the health care system

Compare logistics processes in five private nursing homes

Compare the different healthcare logistics process types investigated and identify the differences and similarities between them.

The overall research objective and specific actions are reflected in the analysis of this study.

The Overall Constructs of the Thesis

The constructs investigated in this research are

1) possible improvement interventions and

2) the decision to implement these interventions.

As explained by Shields (2018), interventions are intended to alter the process design and are implemented to improve the process. Golabi (2018) explained that possible improvement interventions relate to procedures, logistics, technologies and organisational structure, while identified impact factors, which serve as decision criteria, influence the decision to implement the possible improvement interventions and thus have a mediating effect on the decision process. A variation of the links between the constructs depicted in Figure below is applied as an a priori coding, as illustrated by the diagram of Karlsson’s (2016) scheme. This will be discussed in greater detail in the Analysis section.

Constructs investigated in the thesis

The Theory Building in Operations Management (O.M) and Supply Chain Management (S.C.M.)

This PhD project falls within the fields of OM and SCM, particularly logistics management. This thesis is positioned in an OM/SCM/logistics management context and theory building within this field is discussed.

Operations Management and Supply Chain Management

In this research, the design of logistics processes includes technological interventions, process interventions, and their implications for human resources and the structure of an organisation. Theory building within an OM and SCM context and the implications for this study are discussed below. Gammelgaard (2014) suggested that, there are three ‘schools’ in logistics research: the analytical school, the systems school and the actors school, but only the analytical and systems schoolshave produced exemplary cases. The theory is context-specific where it is necessary to analyse and compare the cases to develop new knowledge and explore more strategies to manage the logistics system in the context of health care sector.

Theory Building

According to Wacker (1998), theory consists of four composites. He outlined four steps for ‘good’ theory building, although these might not occur sequentially. These composites and the steps of good theory building are presented in Table, together an explanation of how each composite is applied in this study.

Theory building as applied in this study

In good theory building, systematic similarities, i.e. patterns, are more important than descriptive differences, as explained by Bendassolli (2014), based on Wacker’s (1998) theory. Differences between the investigated case studies are inevitable, but the focus in this study will be on identifying similar patterns across case studies. Testing a theory in a new environment or time period allows it to be built on or extended to new domains. Accordingly, this study tests the theory for different process types and different nationalsettings. Furthermore, integrating existing theory in building theoretical relationships increases the abstraction level of the theory. The literature review included in this study therefore plays an important role in terms of generalising findings. Choi and Wacker’s(2011) paper reviewing the existing literature on OM and SCM offers guidelines for future theory building in the field. Similar to Wacker’s 1998 paper, the authors suggested that, the boundaries of a study should be clearly delineated and that new theory should build on existing literature. Theyalso argued that multiple theoretical perspectives should be integrated in any explanation of an issue and possibly challenge the dominant paradigm (Choi and Wacker 2011). As explained in the literature review, different theoretical streams of literature are integrated in this study: BPM, logistics and SCM, technology assessment and justification, and human factors and organisational management.Wacker(2011) argued that theory building research can be classified as either analytical or empirical in nature and further subdivided into six categories. This study is empirical in nature—specifically, it is an empirical case study. Like the other five subcategories of research, empirical case studies are important for OM theory building, as they are used to propose new theories by testing and developing relationships between variables. Empirical research can be refuted by internal inconsistencies (Wacker 1998). The justification and use of the case study as the research design of this thesis is described in the Research Design section.

The Case Study

The research design chosen for this thesis, the case study, is justified below, and a selection of case studies and arguments for discarding other research designs are provided.

Why thecase study was chosen as the research design for this work. A research design should reflect the nature of the research questions (Karlsson 2016; Yin 2014). The case study was found to be suitable in this instance for the following reasons:

The overall research question is a “how” question (Yin 2014);

The study does not require control of behavioural events;

The research questions focus on contemporary events (Yin 2014);

The lack of maturity in the research field, as revealed by the literature review, makes the case study an appropriate format (Åhlström 2016).

The subject of an investigation dictates the suitability of a research method. Yin (2014) defined a case study as ‘a study that investigates a contemporary phenomenon (the “case”) in depth and in its real-world context, especially when the boundaries between phenomenon and context may not be clearly evident’ (p.). The phenomenon investigated in this study is the logistics process, or, more precisely, the improvement of logistics processes, and the context in which it was investigated is the healthcare context—specifically, a private nursing home. For the purposes of this study it is important to understand the phenomenon in its context, as this is what makes the case study a suitable research method. One of the benefits of case research is the increased possibility of identifying cause and effect (Voss et al.2016). Eisenhardt (2015) argued that the strengths of case study research are its likelihood of generating novel theory, the testability and empirical validity of resulting emergent theories and the ability to identify some of the weaknesses of such research. One such weakness,according to Eisenhardt (2015), is the potential for an overwhelming amount of data, which can lead to overly complex theories or findings which are too narrow in their application.Another weakness, as explained by Shawn (2014), is that case studies does not attempt to address any particular research question; thus has to be justified according to the claim that something about this particular case will generate a genuine addition to knowledge. Selecting case studies.When theory building is based on case studies, case sampling should rely on theoretical rather than random sampling. In theoretical sampling, cases are selected based on the likelihood of the replication or extension of an emergent theory (Eisenhardt 2015). According to Voss et al. (2016) and Yin (2014), case studies are selected based on the principle of literal replication, which predicts similar results, rather than theoretical replication, which produces contrary results. Private nursing homes were chosen as the focus of this case study because it was possible to select a number of such facilities located in the same region (the North East of England). Each case study conducted as a part of this research focused on a specific process. Three case studies were conducted in total: case study A wasa multiple case study of logistics processes; case study Bwas a single case study of the nursing home cleaning process; and case study Cwas a single case study of the nursing home HR process. The purpose of the case study was to learn from what was expected to be best practice in terms of designing high-performing healthcare logistics processes. All of the case studies revealed that there was room for improvement of the processes evaluated;however, to choose an appropriate number of cases, Eisenhardt (2015) suggested using between four to ten cases, soa total of five case studies were conducted for this research. The boundaries of cases and analysis.. The focus was on the internal logistical processes of private nursing homes, which can be viewed as open systems which interact with other and larger systems, e.g. the external supply chain. First-tier agents in the supply chain were considered in some cases (e.g. a regional warehouse in case A), although these facilities were not the main focus of the study. The unit of analysis was the healthcare logistics process, which was exemplified in this study using three types of investigated processes, HR management, logistics and technology. These particular processes were chosen as the subjects of investigation based on discussions with the nursing homes, taking their focuses and needs into consideration as well as the potential for providing a research outcome. The private nursing home cleaning process may not seem like a logistics process at first glance, but it can be viewed as a means of distribution of services. As such, nursing home cleaning is often a task undertaken by the logistics department (Aptel et al. 2009; Pan and Pokharel 2007). Each process type will be described in detail in the Results.

Theory building based on case studies.Case study research is important for the advancement of the OM field (Voss et al. 2016).There has been an increase in the number of qualitative case studies in recent years (Barratt et al. 2011). Case studies have been dismissed by some researchers for not being sufficiently rigorous, but several authors have demonstrated that it is possible to conduct rigorous case research and use them to build theory in theOM field—see, for example, McCutcheon and Meredith (1993), Meredith (1998) and Stuart et al. (2002). The usefulness of case studies in logistics research in particular was also demonstrated by Ellram (1996). Case research is an effective means of understanding a phenomenon utilising both qualitative and quantitative methods (Meredith 1998). As noted in the literature review chapter 1, the most prevalent research method applied in the reviewed healthcare logistics research is case study research, which can be used for exploration, theory building, theory testing, and theory extension/refinement (Voss et al. 2016). Although the maturity level of the research field is low, a small body of pertinent literature does exist. The purpose of this study therefore fits well with theory building. Case studies are excellent for theory building and for providing detailed explanations of best practices (Ellram 1996), both of which will be utilised in this study. In theory building, key constructs are identified and relationships identified between variables (Voss et al. 2016). It is necessary (Miles et al. 2014)—or at least helpful—to have some indication of the constructs (Eisenhardt 1989). In this study, the constructs of logistics, technology, procedure and structure were used a priori for coding data and it is effective under deductive approach for utilising the existing information and theories for further analysis. These four constructs are variations of the themes identified in the literature review and were also identified in a previous study by Jørgensen (2013). For theory-building purposes, the findings are compared to existing theory (Eisenhardt 1989). The underlying variables for each construct were identified based on the case studies. The variables are the underlying impact factors, which can differ in amount and type—for instance, impact factors may differ in importance and some may not apply under certain circumstances. How cases are selected is an important aspect of theory building. Theory building research typically combines multiple data collection methods (Eisenhardt 1989), so cases must be carefully selected and mixed methods applied. The mixed methods approach will be addressed in greater detail later in this chapter. When a similar pattern is found to be present in several cases, the findings are stronger and better grounded in empirical evidence. In case of conflicting patterns, deeper probing into the evidence may bring to light the reasons for the difference(s) or simply indicate randomness (Eisenhardt 1989). Patterns are therefore identified within and across the case studies conductedduring this research. Stuart et al. (2002) argued that valid criticisms of case study research include the risk of becoming a collection of anecdotes, the potential for producing overwhelming amounts of data and the risk of long narratives. Providing a chain of evidence for part of the data may offer a way to convince the reader that all data was treated similarly (Stuart et al. 2002). Some of the main challenges posed by case research were addressed by Eisenhardt and Graebner (2007), including the theoretical sampling of cases, dealing with rich data from interviews, presenting empirical evidence and writing up the emergent theory. They argued that such challenges can be overcomeby carefully justifying theory building, theoretical sampling of cases, limiting informant bias, providing a rich representation of data and clearly stating theoretical arguments (Eisenhardt and Graebner 2007). Finally, the issue of generalisability is one of the most common criticisms of case study research. Ketokivi and Choi (2014) argued that case research is situationally grounded but at the same time seeks a sense of generality, and proposed that the rigor of case research can be ensured by paying attention to contextual idiosyncrasies already apparent at the data collection stage and by providing transparent reasoning.

The Excluded Research Methods

Selecting the case study as the research design for this study meant actively deciding not to use other possible research methods. The reasons for discarding other research methods arepresented below.

Simulation. Jørgensen’s (2013) study, upon which this study builds, is also a case study but was focused on simulation. To move beyond this previous study, simulation was therefore discarded. Survey. Although this study did include a short survey where respondents were asked to assign values to impact factors, the sample was limited and it was not possible to provide statistically significant conclusions. A larger sample size would be needed for a statistical analysis. Surveys and statistical analyses are better suited for more mature research fields (Åhlström 2016), and as revealed in the literature review, healthcare logistics is still in its early stages of development as a field of research. Mathematical modelling. Several of the studies which have been conducted in the field of healthcare logistics have applied mathematical modelling (Volland et al. 2016; Beliën and Forcé 2012; Utley et al. 2003). Mathematical modelling was not suitable for all the RQs investigated in this study, but it was applied to a limited extent as an aspect of the analytic network process (ANP) method. Action research. Applying action research to the case studies would require that the case study nursing homes be willing to make changes during the course of the project, which was not possible in this case. Action research was therefore discarded as a research method for this study. The presented arguments show that although other research designs could have been used for this study, the case study research design provided the best fit with the research questions, maturity of the field, and the circumstances of and possibilities available to the different facilities.

Mixed Method Research

Edmondson and McManus (2007) argued that the state of prior theory and research determine the type of data to collect and the method for collecting data. For a nascent research field, qualitative data is obtained through interviews, observations and documents, whereas for an intermediate research field, both qualitative and quantitative data is collected through interviews, observations and site material (Edmondson and McManus 2007). To ensure methodological fit with the maturity of the field, this study was therefore based on mixed methods research, i.e. qualitative and quantitative data. Johnson et al. (2014) defined mixed methods research as a type of research in which a researcher or team of researchers combines elements of qualitative and quantitative research approaches for the broad purposes of breadth and depth of understanding and corroboration. Creswell and Plano Clark (2011, p.8) provided the following list of situations which warrant a mixed methods research approach:

A single method is not sufficient;

Results need to be explained;

A second method is needed to enhance a primary method;

A theoretical stance needs to be employed; or

An overall research objective can be best addressed with multiple phases or projects.

The primary reason for adopting a mixed methods approach in this study was the enhancement of the primary method by applying a second method, i.e. the quantitative data and analysis enhanced the findings of the qualitative data and analysis. The mixed methods approach begins with choosing either quantitative or qualitative research and then shifts between the two approaches to gain new insights (Golicic and Davis 2012). To gain a deeper understanding of healthcare logistics processes and their potential for improvement, this study started with the qualitative approach and moved on to the quantitative approach. The qualitative data analysis is effective for reviewing the existing information and improves the evaluation for better understanding and this further helps to analyse the quantitative data and information further which fulfilled the research aim. Thus, the qualitative and quantitative methods are applied in an alternating sequence rather than concurrently (Davis et al. 2011). Johnson et al. (2014) distinguished between three types of mixed methods: qualitatively dominant, quantitatively dominant and equal status (Johnson et al. 2007). The mixed methods approach adopted in this thesis is qualitatively dominated. This unequal and sequential approach is what Davis et al. (2011) referred to as initiation, the purpose of which is to use an initial study inform a second study (Golicic and Davis 2012). This is what Creswell and Plano Clark (2011) described as the exploratory sequential design. The application of mixed methods research in the field of SCM is limited but has increased in recent years (Golicic and Davis 2012). SCM being a relatively new field combined with the complexity of the field makes mixed methods research suitable for SCM research because of the new and complex phenomena to be investigated. Thus, Golicic and Davis (2012)argued that mixed methods research has the potential to advance the theoretical field of SCM in a way that is not possible through the application of any one single research method. The benefits and challenges of mixed methods. The main benefits and challenges of mixed methods research are discussed below. In terms of benefits, mixed methods research offers the strengths of both qualitative and quantitative research, each approach thus complementing the weaknesses of the other (Creswell and Plano Clark 2011) and the evidence produced by the two approaches can create synergies when combined (Eisenhardt 1989). The use of different types of data and methods enables triangulation and provides richer and stronger evidence to support the findings of a study (Johnson et al. 2014; Yin 2014;Creswell and Plano Clark 2011). Mixed methods research may also lead to answers and explanations which are more meaningful, provide a better understanding and a fuller picture (Johnson et al. 2014), and ensures the greatest degree of accuracy possible (Sechrest and Sidani 1995). Moreover, mixed methods research may answer more complex research questions which cannot be answered by applying a single method (Yin, 2014; Creswell and Plano Clark 2011). Finally, a more pragmatic and unrestrictive use of research methods is offered, which could potentially reconcile qualitative and quantitative researchers (Creswell and Plano Clark 2011). One of the challenges of mixed methods research is that it requires the researcher to master several types of research methods (Creswell and Plano Clark 2011)—for example, qualitative and quantitative techniques require different skills. This study mainly builds on qualitative data, which was for the most part collected through interviews and observations. During the course of this study, 50 interviewswere conducted in five nursing homes (10 interviews per facility) with staff members, managers and team leadersand five observation sessions were carried out. The quantitative data is limited by comparison, consisting of a few quantitative figures such as the number of beds cleaned in a nursing home, but mainly the ranking of impact factors as decision criteria. The ranking of decision criteria was based on respondents assigning a value on a 0–10 scale according to the importance of the decision criteria for improving healthcare logistics processes. The quantitative analysis conducted did not involve elaborate quantitative techniques but was almost entirely limited to calculating averages and standard deviations. The most technically difficult method used in this study was the Analytic Network Process (ANP) method. However, ANP software was used to compute the results of the ANP model and so did not require sophisticated quantitative analytical skills. The data gathering and analysis therefore mostly required skills within the qualitative domain and were limited for the quantitative domain.

Another challenge of mixed methods research is the additional time and resources (Creswell and Plano Clark 2011) needed for data collection, analysis and interpretation, which is reflected in the number of conducted case studies. A final challenge noted by Creswell and Plano Clark (2011) is the question of convincing others of the rigor of mixed methods research. The application of mixed methods in this research project is presented and discussed below. The types of qualitative data gathered.The qualitative data gathered consists of interviews and observations. All interviews were conducted by the author and the observations were recordedby the author during scheduled sessions. However, it is challenging to collect the appropriate secondary data due to lack of authentic sources, subscription of the journal articles from where it is easy to gather the information. Without effective knowledge and understanding about the research topic, the researcher also finds it difficult to choose appropriate journal and books for collecting the secondary sources of information which are mandatory for further analysis and evaluation. The types of quantitative data gathered.The quantitative data gathered in this study consisted of files containing numeric data, e.g. number of beds cleaned and number of rooms available in a facility. The bulk of quantitative data used in this study related to respondents ranking decision criteria on a 0–10 scale. In one instance, the quantitative data consisted of a pairwise quantitative comparison of decision criteria. The ranking of decision criteria.The identified impact factors were ranked as decision criteria according to their importance in terms of improving healthcare logistics processes. The decision criteria were originally ranked based on a 5-point Likert scale. Likert scales typically offer five or seven points, but in this case, a 5-point scale was used: 10 indicated strong agreement that the impact factor is an important decision criterion for improving healthcare logistics processes, while 0 indicated that the impact factor had no relevance as a decision criterion. Between these two extremes, 1 indicated that the criterion had extremely limited relevance and 5 indicated that the impact factor was of medium relevance. This is effective way to collect actual feedback of the respondents where the participants can express their thoughts and choose effective options as per their perception.

The Analytic Network Process (ANP)

The ANP method is a multi-criteria decision analysis method for quantitatively prioritising possible solutions based on a set of criteria. ANP is used to break down a complex problem to its constituent components and prioritises alternatives based on a pairwise comparison of these components. ANP allows for quantitative assessment of both qualitative and quantitative criteria (Saaty 2004a). The pairwise comparisons are based on either individual or group judgments or actual measures (Saaty and Vargas 2006). ANP is a generalisation of the analytic hierarchy process (AHP) method, which is a special formof ANP (Saaty and Vargas 2006; Saaty 1990). AHP is a linear hierarchy consisting of a goal, criteria and alternatives, which are not interdependent. ANP is a non-linear network, which accounts for an inner dependence within a cluster of elements and an outer dependence between clusters (Saaty 2004a). AHP is easier to apply but requires independent parameters, a condition not required for the ANP method. The ANP method therefore takes feedback loops into account (Saaty and Vargas 2006). For this reason, the ANP method was chosen. For both the ANP and AHP methods, the underlying assumption is that it is easier for people to make pairwise comparisons rather than comparing all decision criteria at once. Based on these pairwise assessments, it is possible to provide an overall prioritisation of alternatives (Saaty and Vargas 2006; Saaty 2004a, 2004b). The alternatives are compared pairwise with respect to each criterion using a scale of intensity. The most dominant element is assigned a value between 1 and 9 according to the scale presented in Table 3.2 and the lesser dominant element is assigned the reciprocal value. Based on the pairwise comparisons, a prioritisation of alternatives was computed using the software Super Decisions (www.superdecisions.com 2016). For a more detailed description of the theory, an abundance of literature is available, e.g. Saaty and Vargas (2006) andSaaty(2004a). In case C, ANP was applied to the framework of impact factors to enable the ranking of possible solutions for the HR processes. The application of the ANP method to the developed framework enabled the ranking of decision criteria. The deputy logistics manager in the nursing home provided pairwise comparisons of decision criteria and alternatives based on their own judgment. The assigned values from the pairwise comparisons were entered into the Super Decisions software (www.superdecisions.com, 2016) and the computed results are presented in the Results chapter.

Quantitative and Qualitative Assessments

The developed framework serves as a decision tool for improving healthcare logistics processes. The tool can be applied to enable either a quantitative, qualitative or combined assessment of interventions and consequent process designs. For example, applying the ANP method to the developed framework would allow for a quantitative assessment of different process solutions, whereas a descriptive report of the elements of the framework would allow for a qualitative comparison of possible process solutions.

Data Collection

Case studies rely on multiple sources of evidence to enable triangulation (Yin 2014). For this study, different types of data were collected by adopting different data collection strategies and gathering data from different nursing homes. For case study A, data was gathered from the five private nursing homes. For case study B, data was mainly gathered from one private nursing home. For case study C, data was gathered from the primary nursing home.

Data collection stages. The data were collected between September 2019 and September 2020. Figureillustrates the timeline for data collection pertaining to each case study. The comparative case studies for the nursing homes, i.e. the case studies investigating the HR management process and the logistics process, all followed the same overall data collection stages: A round of semi-structured interviews and observations, followed by a validation and factor ranking round of either structured interviews or a survey. Guided data collection.The research questions helped identify the relevant information to be collected (Yin 2014, p.30) and the case study protocols were used to guide the collection of data for each case study. The case protocol guidelines provided by Yin included four aspects: A case study overview;the data collection procedures;the data collection questions; and a guide for the case study report (Yin 2014, p.84). The case study protocols for this project included 1) an overview of the people to be interviewed, including their roles, responsibilities and contact details; 2) the preparations necessary prior to the interview/observation session; 3) the background information to inform respondents; 4) the purpose of the interview/observation; 5) the interview questions and interview question categories; 6) particular events, items or occurrences to document for observations; and 7) how to report data. An example of an interview guide is presented in Appendix and an example of an observation guide is presented in Appendix as part of the case study protocol. One of the features of case study research is that data collection and data analysis is guided by theory (Yin 2014). Data is therefore coded according to previously developed constructs, which will be discussed in the section on the coding of qualitative data.

The Interview Approach

As the prejudices, stereotypes and/or perceptions of the researcher cannot be entirely eliminated from semi-structured interviews and may thus alter some responses or cause difficulties in understanding the equivalence of meaning (Blandford 2013).The researcher allowed for long discussions and pauses, which enabled the participants to reflect and give complete insights without rushing in with another question. Furthermore, while doing the interviews, the interviewer took notes and recorded the sessions; these tapes were later transcribed for analysis, as advised by the Open University (2013), which advised that recording interviews allows the interviewer to focus on the interview and develop an understanding with the participants. The aforementioned approaches were applied in order to mitigate any potential errors or biases which arose while conducting the interviews through managing fairness, giving equal opportunity to the respondents and maintaining transparency in collecting the data and information. However, eye contact and face to face interview cannot be conducted which further may ruse misunderstanding among the respondents.

The Pre-Designed Questionnaire

The semi-structured interviews were done using a pre-designed questionnaire.Each question was identified based on the list of objectives to examine the existing theories presented in the literature review chapter of this research. The first section of the questionnaire included general information about the participants in order to create a background for their role and ascertain how long they had worked for the company. The second section of the questionnaire was divided into 3 parts, including the research questions arranged consecutively from Q1 to Q6 and grouped based on the sequence of the objectives (first, second and third) as represented in the table.

Theory building as applied in this study Theory building as applied in this study

Documenting Data

All field work was conducted by the author of the thesis. During the field work, field notes were taken to document interviews and observations. Directly after the field work was carried out, the notes were documented electronically and elaborated through tabular formation of the data as well as information documentation while they were still fresh in the researcher’s mind. The notes were then arranged according to the objectives and themes to provide a logical storyline. The responses from the interviews were transcribed, grouped according to each objective and participant code number, andanalysed to determine the similarities and differences between them where the duration of the interview is approximately 30 minutes. The data from the nursing home performance reports were also be examined to identify the numerical evidence needed to test the existing theories;as was done for the responses from the interviews, the analyses were grouped and categorised according to each objective. Afteranalysing the quantitative and qualitative data, the researcher compared the analysis along with the existing theory to be tested and performed a critical review with reference to each objective to determine the common and different themes present in the data and develop a comprehensive summary of the findings.

Interviews

The interviewees were selected based on their knowledge of the case study process and their knowledge of and access to relevant process data as well as their age, gender and tenure are considered. Open interviews with a flexible agenda were conducted for the preliminary stage of case study A. The semi-structured interviews conducted for the case studies were structured based on previous data and findings. The posed interview questions related to the research questions and mainly considered the challenges in the process, the reasons for implementing interventions such as changes to process steps and the implementation of technologies, the reasons why interventions fail and performance measurement. An example of an interview guide with inherent research questions for the semi-structured interview is presented in Appendix. The format of the structured interviews followed the structure of the survey, an example of which is also provided in Appendix.The interviews lasted between 30 and 90 minutes depending on the subject and interviewee.

Observations

Observations were conducted for each case study to learn about the process, as advised by Blandford (2013). During the observations, some interactionswere initiated to explain what was happening and to obtain the employees’ opinionsregarding their work-related activities. In some cases, the observations were direct observations without interaction, but in most cases some interaction with the employees took place, making the observations participant-observations. Observation sessions lasted between 30 and 90 minutes depending on the activity observed.

Documents

Different types of documents were obtained for the case studies such as journal articles, news published, books and other general articles and online database. Documents providing insights into process performance, standard operating procedures (SOPs), volumes of activities and guidelines for operations were obtained to gain an understanding of the investigated processes. Tables include lists of the documents obtained for each case study.

Data Collection Case Study

HR management data wascollected from the primaryprivate nursing home in three stages: A preliminary stage and a round of semi-structured interviews. Each stage is described below.

The preliminary stage. The preliminary stage was a pilot studyconducted at the primary case nursing home, consisting of 10 open interviews and four direct observation sessions of each stage of the HR management process; documents containing process data and standard operating procedures were also obtained. This is effective to analyse feasibility of the study, cost, duration and improve the study successfully further. The purpose of this preliminary data gathering was to gain an understanding of the HR management process and identify the challenges and improvement opportunities of the process. Although this stage of data collection was originally intended as a pilot study, the data collected was so extensive and of such a quality that it was decided to include the results as one of the multiple case studies. Hence, in this study, effective case study analysis as well as pilot study by taking interview is effective to conduct further analysis and evaluation of the research topic. Semi-structured interviews and observations. A round of semi-structured interviews was conducted with 20 managers at the remaining four case study nursing homes and the duration of the interview is about 30 minutes or sometime more. Thesemanagers were responsible for the HR processesof the case study nursing homes. The data collected at this stage was analysedthrough interview transcript representation as well as evaluating the existing knowledge sand theories about operation management to identify a list of impact factors affecting the decision to improve healthcare logistics processes. The impact factors identified in the previous stage were presented to the managers responsible for the logistics process for validation. Thus, the respondents confirmed the importance of the identified decision criteria for the decision to improve the bed logistics process by assigning a value of 0–10. This stage of data gathering therefore served the purpose of validating and ranking the identified impact factors. An overview of the data gathered for Case Study A is presented in Table, which lists the interviews and observations carried out and the documents obtained from the case study nursing homes.

Data Collection Case Study B

For the nursing home cleaning case, 20 interviews were conducted at one case nursing home and each interview takes about 30 minutes, where the cleaning process was observed on one occasion and several documents were collected. IT staff were also interviewed to learn about the strategy and opinions of the IT department. Staff from the central lean and strategy department were interviewed to learn about continuous improvement efforts in the nursing home and how these might relate to healthcare logistics processes. The purpose of Case Study B was to validate the impact factors identified in Case Study A relating to the nursing home cleaning process and to confirm the track and trace technologies used where the participants are selected ion the basis of random samplings technique in the cleaning department of the nursing home.

Data Collection Case Study C

Four observation sessions of the HR process were conducted. Interviews and observations took place at the primary case nursing home and limited data was obtained from another nursing home to provide perspectives from another setting. Interviews and other observations were conducted.

The Stakeholders and Governance of the PhD Project

During the course of the research project, a number of stakeholders showinterest in the outcome of the project where the general meeting is arranged at the organisations in order to identify the case studies, empower the stakeholders including the deputy managers logistics operation managers and other board of directors in order to conduct the meeting efficiently and analyse the case successfully. The main stakeholders of this project are the primary private nursing homes, as the managers have an interest in the practical implications of the results. Attaining scientific evidence of how to improve the logistics processes of the nursing home, as this type of evidence will resonate with executive managers was a distinct motivation of the logistic managers in participating in this study. During the course of the PhD research, regular meetings were held with the managers and deputy managers of the logistics departments of the nursing home. During these meetings, processes were selected for investigation in the case studies through a joint discussion where own knowledge and skill are effective for auditing the information and utilise authentic and reliable data and interview transcript for further analysis and evaluation. Similar meetings were held to ensure progress and set the direction of the case studies. The ongoing discussions between the researcher and the managers ensured that the issues addressed in the research and its direction was of continued relevance to the ‘real world’, which is a prerequisite for good research (Karlsson 2016). Contacts for each case study were obtained through the manager and deputy manager of the logistics department. Fifty percent of the interviews and observations were carried out with staff from the logistics department, but other departments such as marketing and sales, technical department for managing the organisational data and information, finance team, human resource department were also involved. At the end of each project, project handover and evaluation meetings were held with the same group of stakeholders in order to ensure that,they had access to all the information about the case study, organisational activities and financial capital investment in the logistics operations, acknowledge the findings and develop effective recommendations from the case studies. In the case study, it has been that, the managers focus on maximising the interest iof the stakeholders so that it would be possible to create values for all the stakeholder engaged with the project and retain them for long run for maximising productivity and performance. The employees involved in the investigated processes also have an interest in the outcome of the research, as any changes to the process would affect their work. Thus, these employees have an interest in the way their work is perceived and portrayed. The major interest of the employees are getting high salary payment, incentives and bonus which are monetary rewards that are expected by each employee in the project. On the other hand, the employee’s interest is related to have health and safety at the workplace, supervisor quality, working condition, co-worker relationship at the workplace, which must be maximised by the organisational management team. It was made clear to the employees participating in the research project that the intent was not to report on how they perform as individuals but to suggest how to make their job easier and to hear their ideas for improvement. Connections with the appropriate managers overseeing the case study processes were therefore established through a liaison in the Continuous Improvement (CI) department. The efficient managers were then able to provide access to each nursing home’s employees and data so that the management team can manage the employees and handle the patient’s data and information for better operations and in this regard continuous improvement in managing the operations and logistics are possible through data management, handling stock of the products in the heath care institutions and managing health care ethics. The managers are trying to achieve positive outcome of the projects and manage the health care operations efficiently by proper utilisation of the organisational resources as well asthe employees were advised that the findings from interviews and observations would not be reported back to management. The employees therefore had no motive to portray their work in a certain way.

Analysis

This section describes how the qualitative and quantitative data were analysed for this study.

Analytic strategy. The analytic strategy adopted in this study lies somewhere in between ‘relying on theoretical propositions’ and ‘working data from the “ground up”’ (Yin 2014). The diagrams presented in Figure 3.3 together with the framework developed by Jørgensen (2013) provide a type of a priori codes, which are illustrated in Figure 3.6. The specific impact factors were partly identified by a ‘ground-up’ approach resembling grounded theory (Corbin and Strauss 2015), but they were also compared to the underlying factors of the framework developed by Jørgensen (2013). Analytic techniques. Yin (2016) identified five techniques for analysing data: pattern matching, explanation building, time-series analysis, logic models and cross-case synthesis. This study utilises the pattern matching technique by applying a theoretically based pattern to analyse data. This pattern can be viewed as a type of preliminary framework.Eisenhardt (1989) suggested two other types of analysis: 1) analysing within-case data and 2) searching for cross-case patterns. Both within-case data and cross-case patterns were identified in this study and the analysis therefore resembles a cross-case synthesis in certain ways. The concepts of BPM, logistics and SCM interventions, technological interventions, and organisational interventions indicated in Figure 3.6 were identified in the literature review as types of interventions for improving healthcare logistics processes. The parentheses indicate the constructs which were used in the framework developed in this study. Coding data. According to Miles et al. (2014), codes are ‘labels that assign symbolic meaning to the descriptive or inferential information compiled during a study’ (p. ). Coding, which is used to reduce data into categories, is a type of analysis which enables the interpretation and an understanding of the meaning of data (Miles et al. 2014). Codes are assigned to portions of data to identify reoccurring patterns. In this study, data was coded and recoded in two coding cycles (Miles et al. 2014). The first coding cycle was conducted to identify concepts.The pattern in Figure 3.6 represents the resulting a priori codes and is consistent with Jørgensen’s (2013) framework, which consists of the four constructs of logistics, technologies, structure and procedure and includes the underlying factors relating to each of these constructs.

These underlying factors were compared to the codes drawn from the data, revealing further existing and new codes. In the second cycle of coding, the codes were re-grouped and categorised. This iterative coding process ensured consistency across data and cases. The codes represent the impact factors identified in this study and form the empirical basis for the developed framework. Interview and observation data was coded to reflect challenges, reasons for implementing interventions and the decision criteria applied for interventions. The codes thus represented the factors impacting the design of healthcare logistics processes, which are used as decision criteria for improving healthcare logistics processes according to the needs and preferences of hospitals. The respondents were asked about the applied decision criteria and reasons for implementing changes, as these aspects relate directly to factors impacting the design of healthcare logistics processes. Challenges were included to identify impact factors, as overcoming challenges help improve a process. The quantitative data analysis,For data gathered from the case studies, impact factors were ranked as decision criteria on a 0–10 scale according to their importance for improving healthcare logistics processes. Based on the assigned values, decision criteria were ranked according to process and country setting. Differences in perceived importance amongst respondents within a case and across cases were identified based on the calculated averages and standard deviations. For the cleaning case, the ANP method was applied, first to prioritise alternative solutions and second to prioritise the importance of each decision criterion. The quality of research,Each of the quality aspects of rigorous case study research considered in this study is discussed below, including construct validity, internal validity, ecological validity, external validity (i.e. generalisability) and reliability.

Validity

Construct validity is mainly related to the data-gathering phase and refers to the extent to which a study actually investigates what it claims to (Denzin and Lincoln 1994). Construct validity was ensured through triangulation by gathering and analysing data from different sources and adopting different strategies for data gathering (Voss et al., 2016; Ellram 1996). Different sources of information were accessed, namely managers and employees across different nursing homes, as well as different organisational units within a nursing home. The main strategies adopted for collecting data were interviews and observations. Finally, with regard to construct validity, ensuring coherence between research questions and conclusions by providing an understandable chain of evidence is vital for the internal validity of a study (Yin 2014; Ellram 1996). This chain is evident in the links between each part of this thesis: the Introduction, which explained the motivation for the study and from which the research questions emerged; the Literature Review, which detailed what is already known about the research topic to identify a research gap and justify the current study; the Methodology, which provided a justification and detailsof how the research questions were answered; the Results,where the findings of the study and data linked to the findings were presented; the Discussionpresented the answers to the research questions, leading to the development of the final framework; and lastly the Conclusions covers thefinal observations on the findings of the research. Internal validity, which refers to the causal relationship between variables and results,is only appropriate for explanatory or causal studies and is mainly relevant to the data analysis phase (Yin 2014). Similar findings across studies, i.e. pattern matching, increases internal validity (Yin 2014; Denzin and Lincoln 1994; Eisenhardt 1989). In this study, the findings across cases were compared and similar patterns identified. Addressing rival explanations is vital to improving the internal validity of the study (Yin 2014). In abductive reasoning, the most likely explanation is pursued, which can account for observations. Thus, possible rival explanations are sought and/or discarded as other more compelling explanations emerge (Miles et al. 2014). The developed framework therefore underwent several iterations until the final iteration of the framework was settled. Ecologicalvalidity. When conducting direct observations, the presence of the researcher may affect the behaviour of the people observed. Ecological validity concerns whether research findings are applicable to people’s natural social settings (Bryman 2012). The nursing home employees were aware that they were being observed and were familiar with the purpose of the observation, which was to learn about the steps of and challenges involved in the processes. Thus, it was not individual employees’ performance which was being investigated, but rather the process steps. Furthermore, it was in the employees’ own interest to identify the challenges in the process. However, their fear of being replaced could affect their behaviour and cause them to try to give an impression of higher efficiency than under normal circumstances. The study can be considered as being conducted in a relatively realistic setting and findings are therefore expected to be generalisable to real-life settings. Externalvalidity. External validity is the identification of which domain findings can be generalised. Conducting case study research entails some limitations, such as generalisation issues. Case studies aim for analytic rather than statistical generalisation: The goal is notuniversal generalisability but to determine under which conditions certain outcomes can be predicted (Yin 2014). The generalisation of case studies occurs at a conceptual level, not merely at the level of a specific case. The analytic generalisation of a case study is based on either the advancement of theoretical concepts, e.g. through corroboration, modification or rejection, or on new concepts emerging from the case study (Yin 2014). In this study, analytic generalisation was based on both the advancement of existing concepts and the identification of emerging concepts.

To improve external validity, multiple case studies were conducted. The identification of patterns across cases, e.g. the identification of impact factors in the case studies, enhances external validity (Voss et al. 2016), and the use of a case study protocol improved the external validity of this study (Yin 2014).Thus, each case study generalises findings according to the investigated process and the country setting. Case Study C was generalisable in terms of applying the ANP method to the developed framework. In addition, each case generalises the findings in terms of applying the developed framework to the assessment of technologies or process improvement approaches. Finally, all of the case studies contributed to benchmarking or performance measurement in some way. The contribution to performance measurement is both in terms of defining performance metrics and capturing data. The findings from case studies may apply to other cases which do not strictly match the circumstances of the investigated case (Yin 2014). Matching findings across the conducted case studies made it possible to predict that the findings are likely to apply to nursing homes and healthcare logistics processes other than those specifically investigated in this study.

Reliability

Reliability refers to the extent to which the same results and conclusions would be reached if the study were repeated. Reliability was ensured through colleague review and triangulation (Miles et al., 2014; Eisenhardt 1989). The reliability of this study was enhanced first by the use of a case study protocol (Yin 2014) and second by the transparency of the research process (Voss et al., 2016; McCutcheon and Meredith 1993). A detailed account of the research process and details of the research protocol have therefore been provided, and the link between data and findings through coding is detailed in the Results.

The Natureof Scientific Contributionsand Practical Implications

A theoretical contribution should be both of interest to practice and generalisable (Boer et al. 2015). Thus, the research questions investigated in this study are rooted in both theoretical and practical needs, as argued in the Introduction. Furthermore, the maturity of a research field determines the possible contributions to the field. Edmondson and McManus (2007) distinguished between three levels of theory maturity. First, nascent theory proposes tentative answers to ‘how’ and ‘why’ questions, suggesting new relationships between phenomena in the event of little or no existing theory being available. Second, intermediate theories are based on existing literature and often rely on different streams of literature. Third, mature theories consist of well-developed constructs and models, which have been developed based on extensive research conducted in different settings (Edmondson and McManus 2007). As a realist stance is taken in this study, a contribution ‘consists of a better or more inclusive explanation of observed, or observable, phenomena’ (Boer et al. 2015). Boer et al. (2015) further argued that there are two fundamental ways of contributing to theory: exploratory studies or confirmatory work. Exploratory studies observe and identify phenomena which cannot be explained well enough by existing theory. Confirmatory work puts propositions to the empirical test in a given context. Furthermore, contributions can be less formal in nature, e.g. they may point out flaws in existing theory when applied to a different context or by identifying areas where existing literature is insufficient. In this study, impact factors were identified to explain the decision to implement interventions for improving healthcare logistics processes. Furthermore, the findings were validated by applying a quantitative approach to the initial exploratory qualitative approach. The so-called ‘less formal’ contributions of this study are the findings of the literature review, which mappedthe existing literature on the topic of healthcare logistics and offered an agenda for future research. Finally, a decision framework was developed based on the literature review and the empirical research performed in this study.

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The Research Limitations

The research presented in this thesis is limited to logistical processes within private nursing homes. It primarily concerns the management of materials, but it also addresses the distribution of services to a certain extent. Interventions relating to at least one of the following types are considered: 1) BPM (i.e. changes to process steps); 2) SCM and logistics interventions; 3) technological interventions; and 4) organisational interventions. Other types of interventions, such as the transport and logistics of residents or medicines, residents care plans, medicine consumption or any other medical or social interventions are not considered in this study. In the pandemic era of COVID 19, it is not possible for the researcher to arrange interview session and face to face communication for gathering authentic data and this is one of the major limitations of the research, where the researcher fails to collect relevant data for further in depth analysis and evaluation. During the lock down era, the survey technique is also hampered and online survey is costly for the researcher to conduct. Hereby, lack of time and budget constraint are the major limitations of the research, where the researcher faces difficulties to collect appropriate data and information about the logistics operations of the health care institutions. The private institutional representatives are necessary to be included which is also difficult for the researcher due to such situation of COVID 19.

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Chapter Summary

This chapter details the methodological approach used in this study. A critical realist philosophical stance wasestablished and the implications for the research design were described. The meta-RQ investigated in this study was broken down to three RQs and eight SQs and linked to the research questions investigated in each case study. Case study as research design and mixed methods research as research strategy were justified and described and the procedure for collecting data for each case study was explained in detail. The process of analysing the collected data through coding for qualitative data and the prioritisation of impact factors as decision indicators was outlined. The measures for ensuring the quality of research were described in terms of their validity and reliability, and finally, the nature of scientific contributions and practical implications of this study were characterised.

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