EVALUATING THE MODULAR SUPPLY IN ELDERLY CARE FROM MULTIPLE PERSPECTIVES

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EVALUATING THE MODULAR SUPPLY IN ELDERLY

CARE FROM MULTIPLE PERSPECTIVES

Master thesis, Msc Supply Chain Management

University of Groningen, Faculty of Economics and Business

July 21, 2013

RUOCHEN CHEN

Student number: S2094231

E-mail: r.chen.2@student.rug.nl

Supervisor/university

Drs. M.R. van der Laan

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ABSTRACT

As remarkable competitive advantages have gained from modularity in manufacturing setting, a growing body of literature introduced this concept into healthcare sector recently, especially the elderly care. Although existing literatures theoretically highlight the possible effects of service modularity on various aspects, its performance has not been systematically measured yet. Along with this point, this thesis aims to investigate how to evaluate the performance of service modularity in a specific healthcare setting. The central purpose of this thesis is to develop different instruments to measure the performance of modular service provision in elderly care in relation to multiple

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1. INTRODUCTION

Since product modularity has gained significant benefits in the manufacturing sector, modularity is gaining more attention in service industries recently. Notable authors such as Pekkarinen and Ulkuniemi (2008), Bask et al (2010) and Rahikka et al (2011) indicate that service modularity enables organizations to meet heterogeneous customer demand in a cost efficient manner. Among all the services industries, healthcare service, especially care for elderly people, is recognized as one specific service context in which

organizations need to align customization with efficiency goals (De Blok et al, 2010). Since the population is aging rapidly in most of the developed country, the healthcare system is facing fierce challenges. On the one side, demand driven policies require the healthcare system to put the diverse individual elderly patient’s requirements into a central position. On the other side, healthcare organizations are urged to decrease operation costs (De Blok et al, 2010). Developing a personalized supply for each older patient individually is too costly and time consuming. To balance demand-driven care and costs, a modular service design is largely encouraged into the elderly provision.

Despite the rising importance of service modularity in elderly care, the effect of modularity on performance has not been systematically evaluated (Jacobs et al, 2007; Dörbecker and Böhmann, 2013). Also, in other service contents, the effects of service modularity on various performance dimensions have not been empirically tested. Most of the existing studies focus on the way to modularize service offerings rather than actively evaluating them. In a relatively new research of Dörbecker and Böhmann (2013), the concepts and the effects associated with service modularity presented in the existing literature are summarized and compared. For instance, De Blok et al (2010, 2012) discuss the effects of service modularity on both client involvement and personalization in order to achieve customization. In addition, Lin et al (2010) and Pekkarinen and Ulkuniemi (2008) discuss the effect of service modularity on costs reduction. Although it is undeniable that all these research give considerable insights on the effects of service modularity, a substantial part of these studies treat these effects only on a conceptual level (Dörbecker and Böhmann, 2013). In addition, a more balanced evaluation not only on benefits and risks effects, but also on different perspectives could help to deeply explore the performance of service modularity in practice (Dörbecker and Böhmann, 2013).

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6 case study is helped to gain empirical insights of modular service in an elderly care setting. In the end, proposed instruments are finalized based on empirical evidences and validate measurements in the existing literature. Therefore, the main research question of this thesis is:

How to evaluate the performance of service modularity in elderly care from multiple perspectives (patient, care provider and organization)?

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2. THEORETICAL FRAMEWORK

In this section, the theoretical framework of present research will be elaborated. First, the concept of service modularity is introduced. Second, performance objectives of service modularity are discussed which leads to several sub questions. Third, theoretical

performance indicators are explored from performance objectives, indicating the research scope which forms the theoretical foundations of this research.

2.1 The Concept of Service Modularity

Modularity, as defined by Schilling (2000), is a continuum describing the degree to which a system’s components can be separated and recombined, and it refers both to the tightness of coupling between components and the degree to which the rules of the system architecture enable or prohibit the mixing and matching of components. Notable authors such as Pekkarinen and Ulkuniemi (2008), Voss and Hsuan (2009) ,Bask et al (2010) and Rahikka et al (2011) then extend this concept into service sector. Service modularity is highly associated with the concepts of different terms: “architecture, components, interfaces, modules” (Dörbecker and Böhmann, 2013). Service architecture is the way that the functionalities of the service system are decomposed into individual functional elements to provide the overall services delivered by the system (Voss and Hsuan, 2009). Service components refer to small parts of service which fulfill the specific function, but which are dependent on other parts of functioning (Voss and Hsuan, 2009; De Blok et al, 2010). Interfaces are the linkages shared between different modules (De Blok et al, 2010), that are more “soft” than those in the product modularity by involving extensive interpersonal behaviors. Service modules are understood as functional, self-containing parts which consist out of interdependent components (Schilling, 2000; Voss and Hsuan, 2009). By mixing and matching service modules, final service packages can be customized in various ways to meet customer requirements.

2.2 Performance Objectives of Service Modularity

Performance objectives are crucial to organizations in judging the performance of operations and developing the competitive capabilities. Although the perceived benefits of service modularity have been widely discussed, the performance objectives of service modularity are not explicitly defined in the extant literature. Jacob et al (2007) examined the effects of product modularity on four objectives: cost, quality, flexibility and cycle time. Along with their findings, the following sub sections elaborate the theoretical foundations to investigate linkages between service modularity and performance objectives (flexibility, quality of care, cost and responsiveness).

2.2.1 Service modularity and flexibility

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8 foremost competitive advantage of modularization (Lin and Pekkarinen, 2011;

Pekkarinen and Ulkuniemi, 2008; Rahikka et al, 2011). Therefore, the need to

empirically assess the effect of service modularity on flexibility is demanding. However, fewer instruments are available to measure the flexibility in service sector (Purbey et al, 2007). Slack (1991) identified two dimensions of flexibility for manufacturing sector, in terms of range and response flexibility. Range flexibility is understood as to what extent the service can be changed, while the response flexibility is understood as the ease (in terms of cost, time, or both) with which the service can be changed (Purbey et al, 2007). Purbey et al (2007) then suggest measures should be related to these two dimensions in order to assess the flexibility capability comprehensively.

Service modularity is expected to have an impact on flexibility in various ways. Range flexibility is increased by means of service modularity. As Schilling and Steensma (2001) state, modularity is a tightly integrated hierarchy which replaced by loosely-coupled networks that allow components to be flexibly recombined into various configurations. By mixing and matching of service modules (De Blok et al, 2010), variation in service package is created to meet the diversity clients’ needs. As such, service modularity is associated with an increase in range flexibility by achieving customization in service offerings, which enables organizations to server a wider range of customers (De Blok et

al, 2010). Moreover, De Blok et al (2010) observe that not only does the client

involvement take place but the intensity increases in the late stage of specification process to advance the modular service offering from low to high customization. Modularization allows clients adapting standard modules to truly integrate their

preferences and requirements (De Blok et al, 2010), which consequently achieves a high level of customization in the late offering creation stage and subsequently increases the capability of range flexibility. De Blok et al (2010) then state service components and modules are easier to adapt than product components and modules, that because service components and modules can quickly be changed through extensive interactions between clients and providers. Due to closely interact with clients, service providers use their interpersonal behaviors not only adapt the content of service modules but also alter the way of service delivery to achieve customization in service offering. These interpersonal behaviors refer to personalization is the result of interactive nature of care, which

effectuate customization in modular service delivery process. In this way,

personalization is better accommodated by means of service modularity that consequently increases the range and response flexibility. However, Rahikka et al (2011) argue that if the content and process of service module change, organizations should carefully balance the incurred costs and extra time and the increase of flexibility. Therefore, instrument is needed to assess the effect of service modularity on flexibility in terms of incurred costs and time, which leads to following sub question:

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9 2.2.2 Service modularity and cost

Besides flexibility, lower cost is the second compelling advantage that widely discussed in the existing literature on modularity. Along with the growth of innovative care service, more attentions are gained in the effectiveness and efficiency of delivery in healthcare settings. This implies that care providers and organization managers require an

understanding not only of the efficacy of their interventions and services, but also of the relative value in an economic sense of their efforts (Zilberberg and Shorr, 2010). When examining the extant literature, it is found that most of researchers agree that modularization in service leads to lower costs by standardizing interfaces and

rationalizing service and process design (De Blok et al, 2010; Pekkarinen and Ulkuniemi, 2008; Bottcher and Klinger, 2011). Bask et al (2010, 2011) theoretically report that service modularity results in standardized interfaces. Pekkarinen and Ulkuniemi (2008) then emphasize modularity as a means to rationalize the work process, thus, achieve profitability. In service provision, interfaces could be visualized as the coordination practices among different providers, such as multi-functional meetings or discussions, which aim at managing interdependencies among various service modules. Since service modularity standardizes the interface, coordination of providers’ operational activities between different service modules is expected to be reduced. In addition, modularization in service also allows providers offering services based on structured instructions through standard work routines, which increases work efficiency as well as reduces coordination efforts. Along with this point, Bottcher and Klinger (2011) contend that the

standardization in both interfaces and delivery processes allow a better controllability of the human element in service provision, resulting less coordination efforts. Because less coordination activities results, costs spend on arrange these activities is expected to be reduced. According to Broekhuis and van Donk (2011), in a healthcare setting, non-standardized ways of coordination is demanding due to the increasing specialization of specific patient group and the functional specialization in care. As elderly patient is a specific patient group which holds diverse requirements, the needs of standardized

coordination activities seems very limited. However, by means of service modularity, less coordination efforts might be achieved which consequently reduce coordination costs. Based on these points, the present research mainly focuses to investigate whether service modularity could reduce coordination effects and costs in elderly care setting, which leads to the following sub question:

Sub question 2: How to measure the effect of modularizing service offerings on coordination costs?

2.2.3 Service modularity and quality of care

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10 173). This concept contains many dimensions which depending on the perspective used. For patients, the focus is mainly on effectiveness, accessibility of care and consistent information provided. For care providers, the focus is on the delivery of effective care according to the appropriate standards for their patients. For healthcare organization managers, efficiency and safety of care are main issues (Kuijpers, et al, 2013). Hence, good quality of care can be defined as ‘care of a high standard that is effective, efficient, safe and patient oriented’ (Kuijpers, et al, 2013).

Existing literature does not clearly indicate the effect of service modularity on quality of care. Lin and Pekkarinen (2011) only state the quality of service will be ensured and improved by visualizing and standardizing the service components and interfaces. This means that modularization in service enables service providers not only to fulfill the customers’ needs in an effective and efficient way, but also to optimize the content of service easily. In this way, the service quality is expected to be guaranteed to a large extent. The present research focus on the evaluation of modular service performance in healthcare setting, service quality therefore can be measured by quality of care (Purbey et

al, 2007). According to Sixma et al (2000), quality of care is generally measured from

patients’ view by means of patient satisfaction assessment. In principle, the patient satisfaction measurements could be one way to evaluate the effect of modular service on the quality of care. However, empirical evidence is needed to clarify how the quality of care should be measured in a content based modular supply, which leads to the following sub question:

Sub question 3: How to measure the effect of modularizing service offerings on quality of care?

2.2.4 Service modularity and responsiveness

Responsiveness is regarded as one dimension to assess the delivery performance. It could be visualized by manufacturing cycle time (Jacobs et al, 2007). A substantial part of literature in production operation has suggested that cycle time is reduced by using modular design principles (Jacobs et al, 2007). In service modularity, the cycle time could be interpreted as the total time spent in the development and delivery process of each service package. Kazemi et al (2011) indicate service modules can be easily reused in various contexts and could be composed to fulfill customers’ requirements quickly. Pekkarinen and Ulkuniemi (2008) and Lin et al (2010) then state modularization

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11 totally destroying old service designs (Ho et al, 2009). In this way, modularization in service is expected to decrease the time spend on service offering development and delivery, which subsequently increases the responsiveness. To systematically measure the effect of service modularity on responsiveness, the following sub question is proposed:

Sub question 4: How to measure the effect of modularizing service offerings on the cycle time of service delivery?

2.3 Performance Indicators of Service Modularity

Performance indicators (PIs) are means to help organizations measuring the operation performance by comparing actual results with preset objectives (Fortuin, 1988). In

general, performance indicators do not constitute a precisely defined category (Berg et al, 2005). As Fortuin(1988) indicated, good performance indicators are derived from the organization’s objectives, which means an organization should define its objectives and then operationalize these objectives into suitable indicators. Along with this point, the theoretical performance indicators of service modularity are derived from those

objectives mentioned in the sections 2.2. Conceptually, performance indicators presented in Table 1 are ways that enable organizations to achieve correspondent objectives. These indicators provide directions for instrument development in the following sections.

TABLE 1: An overview of theoretical performance indicators

2.4 Criteria for Performance Measures Development of Service Modularity 2.4.1 Involving various perspectives

Campbell et al (2003) indicate stakeholder perspectives which intended to be reflected by indicators should be taken into account when developing appropriate measures. Loeb (2004) further cites that a significant part of the challenge in measuring health care performance derives from the disparate nature and variable perspectives represented among the key stakeholders. However, despite the wide recognition of the importance of

Performance objective

Theoretical performance indicator

Flexibility Customization of service offering

(De Blok et al 2010, Rahikka et al 2011, Pekkarinen and Ulkuniemi ,2008)

The intensity of client involvement (De Blok et al ,2010)

Personalization in service delivery process (De Blok et al, 2012)

Cost Coordination costs

(Pekkarinen and Ulkuniemi, 2008)

Quality of care Patient satisfaction

(Sixma et al,2000)

Responsiveness Cycle time of service delivery

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12 responding to a variety of stakeholder perspectives when measuring performance, few studies have actually involved these perspectives in the performance measurement

development (Tregunno et al, 2004). To develop a comprehensive evaluation instruments for service modularity, multiple stakeholder perspectives are taken into account and reflected by sets of performance indicators.

In general, patient, care provider and organization are proposed as three important

stakeholders in healthcare system. Firstly, as several proposals on the care provision have put patients rather than the care supplier at the center of processes (Broekhuis et al, 2009), their experiences are important to measure the performance of care. In this research, the frequent users of modular service are elderly people. They are therefore considered as experts by virtue of their greater experience in evaluating the performance of modular service (Sixma et al, 1998). Secondly, care providers are those who work with service modules on the daily basis. They also work as interfaces that link various service

modules together to finalize the service package on patient specifications. With regard to care providers’ opinion, one could get a more balanced evaluation of modular service. Thirdly, besides responsible for the design and delivery process of modular service, healthcare organization are carefully balanced the costs and benefits of the modular care outcomes. Involving the organization’s perspective will get an overall understanding about how to develop the measurement instruments. Based on these points, all these three perspectives are taken into account when developing measurement tools of service

modularity in the present research.

2.4.2 Standardizing measurements development

A central issue in performance measurement remains the absence of guidelines with respect to what to be measured (Loeb, 2004). One needs to understand what to be

measured firstly, and then ascertaining how these measurements should be developed on the basis of the available internal or external data (Loeb, 2004). As measures such as indicators and instruments have become so numerous in recent years, collaborative efforts are needed to standardize these measures (Adair et al, 2006). In the work of Adair

et al (2006), catalogued criteria conceptually for measurements development from

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13 TABLE 2: Criteria for performance measurements development

Criterion Description

Evidence based Measures are valid and reliable operational definitions for the measure that have been demonstrated through rigorous research Strategic Measures direct attention towards the desired change

Important Measures address important or serious health services problem Actionable Measures address a service area that can benefit from

improvement

Feasible Data collection, reporting and follow-through are cost effective Relevant &Meaningful Measures are relevant to key stakeholders

Understandable Measures are easy to understand

Balanced Measures are balanced across types of treatments, treatment setting, major problems, age groups and levels of healthcare system.

Non-ambiguous Measures are clear in terms of which direction for service change is desirable

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3. METHODOLOGY

This section will present the used research methodology, the research design, the source of data, and in the end the type of data analysis performed.

3.1 Research Design

A mixed methodology of design science research and a case study was used in this research. This is because, firstly, this research aims to solve a practical problem by developing an evaluation instrument to measure the performance of modular care. Under this circumstance, the design method was appropriate because it guided the design of interventions or the development of performance measurement of existing entity by using scientific knowledge (Aken, 2004). Secondly, because of the exploratory character of the research objective, a subjectivist, qualitative case study was chosen to gain richer empirical understandings (Rahikka et al, 2011). One advantage of using a mixed method was to combine the strengths of these two different methods. The design science clearly indicated several topics that should be investigated in this research, while the case study not only provided a specific research setting to employ the design method but also enriched the empirical understandings about the evaluation of modular service performance in practice.

3.1.1 Case study setting

A qualitative exploratory case study was conducted in a Dutch healthcare setting to gain an in-depth of observation of research problem. Three criteria were used to select the suitable organization. Firstly, the nature of the services had to correspond to the understanding of modular services (Rahikka et al, 2011), which means the modular

services in selected organization has already designed and applied into practice. Secondly, the case study took place in the context of elderly care provision where a wide variety of heterogeneous services were provided to fulfill elderly clients’ needs (De Blok et al, 2010). Thirdly, the need of measuring the modular care performance was called for in the selected organization. Based on these criteria, a healthcare center in the Northern part of the Netherlands was chosen. This center has already developed several diagnostic and treatment modules, which are now putting into practice. It aimed to offer various customized services and care packages in order to satisfy the elderly client in a low cost manner. However, due to the absence of measurement instrument, the performance of modular service has not been systematically evaluated yet.

3.1.2 Design research

Research activities in present research were mainly focused in the first two topics of the design method structure proposed by Wieringa (2007), in terms of the problem

investigation and solution design. The theoretical performance indicators were explored in a case study setting to gain substantial empirical evidences about performance

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15 developed based upon this case study and available measurement tools in the literature to answer the main and sub research questions.

3.2 Data Source

Two types of data were used for measurement instrument development in this research. One was the valid and reliable measurement instruments in the existing literature that relevant to either the modularity performance measurement or healthcare performance measurement, the other was the qualitative data collected from case study. Existing instruments were the fundaments of the measurement instrument development in this research. They gave directions about which items or what kinds of questions were

appropriate to assess the effects of service modularity. Empirical evidences which gained through collected qualitative data were used to transform these items or questions into a more content based measurement tools.

3.2.1 Case study

The qualitative data was collected mainly from semi- structured interviews. Several open-ended questions with respect to the interviewees’ experiences of modular service were asked during the interviews. Interviewees should be selected from those who work in different functions, activities and organization level in the modular care provision. As a result, three interviewees were selected: organization manager, specialist nurse and a planner in the center. All interviews were conducted by at least two researchers to ensure unity in style and form of interviewing (De Blok et al, 2010) and to reduce the bias of the research. The duration time for an interview is normally within two hours on average. All interviews were recorded by digital devices and then transcribed for further analysis. Moreover, relevant documents (e.g. process description, handbooks) which directly got from the center were needed to translate into English. In the end, all these recordings and documents enabled the researcher to summary the relevant findings.

Valid measurement instruments were obtained from published researches by the means of electronic database- (EBSCO host) and internet (Google scholar) search. Articles were selected based on the following criteria: (1) English-language and were published

between 2000 and 2011; (2) must focus on either the product modularity evaluation or the healthcare performance evaluation. The database and internet search were conducted by using any combinations of search terms shown in Table 3 to obtain appropriate

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16 TABLE 3: An overview of search terms with correspondent performance objectives

Performance objectives Search terms

Flexibility modularity; service; flexibility; customization; customer involvement; elderly care; performance measures

Cost modularity; service; cost reduction; coordination practice; healthcare

Quality of care modularity; service; quality of care; patient satisfaction; elderly care

Responsiveness modularity; service; delivery performance; cycle time; responsiveness

3.3 Data Analysis 3.3.1 Case study

The main aim of analyzing the qualitative data was to explore the concepts of service modularity in a service setting. To be specific, the primary qualitative data in the

interview transcripts and translated documents was analyzed and then related to different performance objectives. Afterwards, key findings and relevant concepts about how service modularity influence different performance objectives were abstracted from these primary data. The key findings not only created a better understanding about the practical meanings of abstract terms, such as modularity, interface and performance but also helped to further transform these abstract terms into the development process of a more content specific measurement tools.

Available measurement instruments were obtained from those selected researches based on the search strategy. By comparing these available instruments, final selection was made based on the following criteria: (1) selected instruments must focus on measuring either the performance of modularity or the healthcare performance; (2) selected

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4. RESULTS

This section will present the results of how the theoretical performance indicators are translated into a specific research setting and how different measurement instruments are developed with correspond performance objectives and stakeholders’ perspective. Also, illustrations of how to use the developed measurement instruments are given in the end. 4.1 How to Measure the Effect of Modularizing Service Offerings on Flexibility? 4.1.1 Performance indicator development

Reviewing the Table 1, three theoretical performance indicators were proposed to measure the flexibility in modular supply. The first indicator is the customization in service offering. It enables organizations to adapt the provision of care to meet the changing needs of elderly and consequently achieve flexibility. During the interview, both the organization manager and care provider expressed their viewpoints on this indicator. The organization manager stated: “...Although it is time consuming and costly

to provide personalized care to each individual elderly patient, our center still strives to offer various customized modular services in fulfilling heterogeneous requirements . Realizing customization in service offering facilities the flexibility…” The care provider

stated: “...modular supply leaves rooms for the customized configuration in service and

subsequently gains an ability to change and adapt service offering easily. Specifically, by modularizing care service, I could choose the most suitable service components from a standard menu and then adapted them based on the needs of an individual patient …”

The second indicator is the intensity of client involvement. To advance the service offering from low to high, the intensity of this involvement is expected to be increased in the late stage. This standpoint was strengthened by the care provider: “…As the elderly

people are frail with special needs, I try to support and let them involved in making their own service package. In the early stage of the process, the interaction with elderly people is restricted to the need assessment. Interactions are increased when customizing care service package in the late stage… ”

The third indicator is the personalization in the service delivery process. During the interaction with the elderly patients, care providers modify not only the contents of service package but also their interpersonal behavior to achieve a better fit with the clients’ needs. In this way, customization will be easily reached and flexibility will be subsequently accomplished. The care provider acknowledged this standpoint:

“...Modifications of the modular service packages were observed in my work. Based on

the records from GP and questionnaire results, I choose several standard questions to begin the conversation. During the conversion, I always fine-tuned the service package on the basis of elderly patients’ needs. In this way, the service package will be very flexible and personalized...” In sum, all three theoretical performance indicators were

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18 4.1.2 Instrument development

Instrument for measuring flexibility should be developed based on the validate measures which were obtained in the selected articles that based on the search strategy. As a result, measures in the works of Worren et al (2002), Duray et al (2000) and Tu et al (2004) were selected. Worren et al (2002) measured the effect of modularity on strategic flexibility and firm performance in the home appliance industry. Duray et al (2000) analyzed how the customer involvement in modularity to realize customization. They proposed several construct variables in term of customer involvement and modularity. Tu

el al (2004) measured the impact of modularity based manufacturing practice on

customization. The validate instrument for measuring customization in their research was therefore used. However, all these three researches measured the effect of product

modularity on performance dimensions. Selected measures were therefore fine-tuned to measure the service modularity performance. Since the present research aims to measure how the modular service affects the performance, open-ended measurement questions or items were suitable to developed base on the existing measures in work of Worren et al (2002), Duray et al (2000) and Tu et al (2004). Table 4 and 5 show the developed

questions to assess the capability of being flexible in modular care offerings and delivery process. These questions should be conducted with organization manager and care providers perspectives respectively. Table 6 shows questions to measure these three performance indicators from the patient perspective.

TABLE 4: Questions to assess the effect of service modularity on flexibility from organization perspectives

Questions

Customization in service offering (Tu et al, 2004; Worren et al ,2002)

How does modular service affect the capability of customizing the service offering to a large scale?

How does modular service affect the capability of responding to customization requirements quickly?

Do the standardized service modules encourage the innovation and flexibility of final service offering? And how?

To what extant is the content of service module easily adapted to the specific needs of the client?

How does your organization balance the high degree of customization in modular service offering and incurred costs and time?

Client involvement (Duray et al, 2000)

How does the intensity of client involvement influence the customization of modular service offering?

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19 TABLE 5: Questions to assess the effect of service modularity on flexibility from

care provider perspectives

Questions

Customization in service offering (Tu et al, 2004; Worren et al ,2002) How is the variation in service offering achieved by means of service modularity? To what extent are service modules flexible to mix and match in configuring various service offering?

Personalization in service delivery (Worren et al, 2002; Duray et al, 2000) How does your interpersonal behavior influence the customization of service offering in modular supply?

How are choice options added to finalize service offering in delivery process? How do your balance the adaptations of service modules or components and incurred costs and time when achieving a high degree of customization in modular service offering?

To what extant are the content and process of service module easily adapted to the specific needs of the client?

When and how does the client involvement take place in modular supply?

How does client specify the features and choices of service module when finalizing his or her service offerings?

To what extent is the client himself or herself actively involved in developing their service offerings?

How does the intensity of client involvement in modular supply affect the variation in service offering?

TABLE 6: Questions to assess the effect of service modularity on flexibility from patient perspective

Questions

Customization in service offering (Tu et al, 2004)

To what extent is your service offering flexible to cover all your requirements? Can your service offering be customized by adding service modules as requested? Are service modules flexible enough that can be combined in various ways to suit your needs?

Personalization in service delivery (Worren et al, 2002; Duray et al, 2000) How do the content of the service offering be altered into your specification during delivery process?

How is the choice options of service module provided to you in modular supply? Do you specify the features and choices of service module when developing your own service offering?

When and how do care providers involve you in the service package configuration process?

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20 4.2 How to Measure the Effect of Modularizing Service Offerings on Coordination Costs?

4.2.1 Performance indicator development

During the interview, the care provider explained that there was barely any coordination between her and other care providers. She also pointed out that modularizing the service enabled her to standardize the work content and process by using standard instructions. In this way, she could work in a more efficient way in her own domain. Consequently, less coordination practices among different care providers, such as multi-functional meetings or unstructured supervision practice, are expected which theoretically leads to less coordination costs. Since the present research only focuses on how service modularity influences the coordination costs, it is proposed as the appropriate performance indicator. 4.2.2 Instrument development

Instrument for measuring coordination costs should be developed based on the validate measures which were obtained in the selected articles that based on the search strategy. As a result, measures in the works of Broehuis and van Donk (2011), Jacob et al (2007), Worren et al (2002) were selected. Broehuis and van Donk (2011) measured the

coordination practices among care providers in the hospital setting from the following aspects: unstructured oral and structured coordination; supervision practice; feedback reporting and standardized work process. Part of the measurable items in the work of Worren et al (2002) was used to assess the standardization in modular process. In the research of Jacob et al (2007), measurable items were used to evaluate the cost

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21 TABLE 7: Questions to assess coordination practices from care provider

perspective

Questions

Coordination practice ( Broehuis and van Donk, 2011) Within a service module

To what extent does the modular service help care providers to coordinate their work within a service module?

How does modular service affect the coordination practices, in terms of unstructured oral consultations, structured coordination meetings, supervision practice within a service module?

To what extent does the work processes standardized within a service module by means of service modularity?

How often do you discuss the feedback and advices with other care providers within a service module?

To what extent are service modules standardized?

Between service modules

To what extent does the modular service help care providers to coordinate their work between service modules to finalize service offerings?

How does modular service affect the coordination practices, in terms of unstructured oral consultations, structured coordination meetings, supervision practice between service modules?

How often do you discuss the feedback and advices with other care providers between service modules?

TABLE 8: Questions to assess the effect of service modularity on coordination cost from organization perspective

Questions

Coordination practice and costs (Worren et al, 2002)

How does modular service affect the coordination practice and cost in your organization? (E.g. coordination costs might spend on arranging multifunction meetings, contact costs with different care providers, etc.)

To what extent are service modules standardized?

To what extent are work processes standardized in modular supply? And how does the standardization of work processes affect costs?

 Are process steps of different service modules documented in modular supply?  Does your organization have a formal procedure to analyze client needs and

define their specifications in service package development process?  Does your organization have standard procedures for transferring client

information across different service modules?

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22 4.3 How to Measure the Effect of Modularizing Service Offerings on Quality of Care? 4.3.1 Performance indicator development

As it is mentioned earlier, quality of care is a broader and complex concept which contains multiple dimensions and definitions. It is important to understand the meanings of quality of care in modular supply and to investigate from which aspects to measure it. The organization manager gave us some clues towards these questions: “…The modular

service is supplied to the patient centered care. Elderly patients could be one important perspective to measure the quality of care in modular service. From the information that I had, the quality measurement could be developed on the basis of CQI in the Netherland healthcare system. However, we need to well-turned the standard CQI measurements into the content of modular service in elderly care provision.”

4.3.2 Instrument development

Based on the finding of the case study, the instrument for measuring the quality of modular care was developed based on Consumer Quality Index (CQ-index) survey. This is a standardized survey to assess the patient experiences towards healthcare treatment, which involves different stakeholders’ perspectives: (1) consumers who are more and more expected to act as informed and critical decision makers; (2) healthcare providers who monitor their provided care service; (3) healthcare organization which supervises healthcare quality; (4) health insurance companies (5) patient organizations which represent patients’ interests and needs (Damman et al, 2009). Returning to Table 1, the theoretical performance indicator for measuring quality of care was the patient

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23 4.4 How to Measure the Effect of Modularizing Service Offerings on the Cycle Time of Service delivery?

4.4.1 Performance indicator development

The reusability of service modules allows organization to develop various service packages in a short time. Consequently, as the service development time decreased, the service offering could be delivered faster than before. Regarding to this standpoint, the organization manager commented: “Due to elderly patients were very busy, we wanted to

provide the ‘one stop’ service to the elderly. It means to provide all needed service modules together in a quick response.” Under this circumstance, a fast delivery of the

service package is relatively important. Therefore, the performance indicator for

measuring the responsiveness in modular supply was the cycle time for service offering delivery.

4.4.2 Instrument development

The instrument for measuring the effect of service modularity on responsiveness was developed based on the works of Jacob et al (2007) and Menor et al (2002). Menor et al (2002) mentioned quantitative measurements to evaluate the new service development performance. Jacob et al (2007) proposed several measures to assess the delivery

performance of product modularity. Measurable items and questions were developed base on these existing measurements to assess the responsiveness in modular service offerings. Table 9 and Table 10 present the measurable items and questions to assess the effects of service modularity on cycle time of service offering delivery. Since organization and care providers are responsible for the modular service development and delivery respectively, items in Table 9 should be measured from an organization perspective while questions in Table 10 should be conducted with care providers. From patient perspective, the cycle time of service offing delivery could be assessed by their waiting time experiences in modular supply. Table 11 shows proposed questions to assess patients’ waiting time experiences.

TABLE 9: Items and questions to assess the effect of service modularity on the cycle time of service delivery from organization perspective

Measurable items of service offering development time (Menor et al, 2002)

Average time for individual service offering development Average time for keep the client waited

The conjunction time between different modules

The time for adjust or adopt service modules on the basis of client requirement

Questions

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24 Does service modularity shorten the development time for service offering? If yes, please indicate how this is realized?

TABLE 10: Questions to assess the effect of service modularity on the cycle time of service offering delivery from care provider perspective

Questions

Cycle time of service offering delivery

To what extent do care providers use similar components in different service modules? (E.g., care provider could switch quickly to different minimal service modules based on similarities of service components )

To what extent do care providers use similar service modules in different service

offerings? (E.g., in the center, care provider re-uses the basic module to configure various offerings in relation to different elderly patient requirements.)

How does the reusability of common components or modules influence the cycle time of service offering delivery?

TABLE 11: Questions to assess the effect of service modularity on the cycle time of service offering delivery from patient perspective

Questions

Cycle time of service offering delivery

To what extent is your service offering delivered on time by means of service modularity?

To what extent does modular supply affect the waiting time between different appointments?

4.5 How to Use Developed Measurement Instruments?

Based on the proposed questions and items, measurement instruments for evaluating the performance of modular service form multiple perspectives, in terms of patient, care providers and organization, are shown in Appendix A, B and C respectively. The target group for these measurement instruments is the entire field of organizations that want to work with modular care. Given the evaluation of service modularity performance is in the early and exploratory stage, developed measurement instruments are used for case

research purpose. When conducting case studies in sampling organizations, these instruments can be used as interview protocols to collect rich qualitative data through semi-structured interviews with multiple respondents from three groups, in terms of patient group, care provider group and organization representative group. Respondents selected from these three groups should be either experienced modular services or

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25 used in interviewing with large amount of potential respondents. Qualitative data

collected from semi-structured interviews should be coded and interpreted to generate relevant findings on performance of service modularity.

In contrast to developed measurement instruments in Appendix A, B& C, the pilot CQI instrument in Appendix D is used for a survey purpose, which can be employed in follow-up studies. The population of respondents for this instrument refers to all patients who were received modular services in the whole year (e.g.in 2013). Respondents should able to recall their experiences with respect to quality of care in modular supply. The sample refers to the patient who has recently received modular service within a certain period (e.g. within 6 months). Researcher could determine the sample size according to the probability of making a type I error (α), the statistical power (1-β) and the effect size (Karlsson, 2009). According to Karlsson (2009), the α level fixed at 0.05 and a statistical power of 0.8 are common practices in operation management, while the effect size can assumed to be fixed at some unknown value (e,g, if the effect size is assumed to be fixed at medium association, then the sample size should at least be 44 respondents). Pilot testing is conducted with a group of potential respondents (e.g. 10 patients) to examine and modify the measurement properties of the CQI questionnaire (Karlsson, 2009). Then, the adapted CQI questionnaire will be filled by sample respondents to collect the

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5. DISCUSSION

This research investigates how the effects of service modularity on various performance dimensions should be measured from multiple perspectives. To achieve this, different measurement instruments were developed in results section. This section will first relate these measurement instruments to the criteria mentioned in section 2.4. Second, it will subsequently discuss how the preliminary data that collected through these instruments will be analyzed and interpreted. Third, it will further discuss how to gain a more balanced evaluation of service modularity on the basis of existing results.

5.1 Relate Measurement Instruments to the Criteria of Performance Measurement Development

Returning to Table 2.2, catalogued criteria that abstracted from the work of Adair et al (2006) are used to assessing the developed measurement instruments in this sub section. First, measurement instruments are developed in relation to multiple stakeholders’ perspectives, in terms of patient, care provider and organizational. It is expected all these three stakeholders have their contributions in supporting modular service provision. Their views may have implications for a thorough evaluation of service modularity on

performance dimensions. Along with this point, proposed questions and measurable items are relevant and meaningful to key stakeholders. Second, instruments are developed base on both valid measurable items in existing literature and qualitative data collected from case study. Validity and reliability of proposed measures are therefore ensured through rigorous research, while feasibility of these measures is enlarged through case study. In this way, measurement instruments are developed in an evidence-based manner. Third, the case study also help to transform and adapt those abstract items in existing

instruments to a modular service based content, which makes the developed questions and items important and actionable in practices. Further, present research clearly illustrates how these questions and items are developed and how to use them to obtain preliminary data, which implies they are understandable and unambiguous. However, proposed questions and items are less sensitive towards the desired change result in evaluating the performance of service modularity. Besides, these questions are failed to develop in a more balanced view across different care groups or organization settings. 5.2 How to Analysis the Data Collected from Developed measurement Instruments? Section 4.5 generally illustrates how to use developed measurement instruments to collect data, while this sub section further discusses how to analysis the collected data. To

evaluate the performance of service modularity, developed measurement instruments in present research are suggested to be used as interview protocols to conduct case studies in modular care organizations. However, these instruments are developed to measure

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27 representatives, 10 care providers and 25 patients respectively within a healthcare

organization. Since one care provider can provide the same modular services to several different patients, care providers and patients are interrelated to each other. Similar, organizational representatives and care providers also interactively cooperate in modular care provision process. Moreover, all three kinds of respondents belong to different hierarchies within an organization. Figure 1 presents an example of how these three kinds of respondents related within an organization.

Figure 1: An example of how three kinds of respondents related within an organization

When conducting interviews with respondents who are interrelated and belong to multiple levels, the qualitative data will be collected in a nested structure. In order to analyze these nested-structure data, it is suggested that researcher could divide

correspondent respondents into several focus groups. One issue in interpreting these data is how to deal with the divergences among key stakeholders’ perspectives towards the same performance dimension. For instances, when assessing the effect of service modularity on flexibility dimension, patients may report that there is hardly any

flexibility found in modular service provision, however, care provider and organization may report that a higher degree of flexibility is achieved in their modular services. Under the circumstances, researchers need to carefully trade-off different key stakeholders’ opinions in order to gain a comprehensive evaluation of service modularity performance. If only considers patients’ opinions to assess the effect of service modularity on

flexibility, cost factors will be omitted. Similar, a higher degree of flexibility will be hardly achieved if only considers organizational opinions. Therefore, it is recommended that researcher need to balanced key stakeholders’ opinions when assessing the effects of service modularity on various performance dimensions. This sub section roughly

discusses possible issues that researcher may encounter when analyzing qualitative data. Even though it provides practical insights of developed measurement instruments, more researches are needed to investigate how to systematically interpret qualitative data which presents in a nested structure.

5.3 How to Gain a Balanced View of Service Modularity Performance? Recall to the main objective of present research, a balanced view of evaluating the performance of service modularity should not only focus on different stakeholders’

Organization level

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28 perspectives, but also on both positive and negative effects of modular supply. However, there is little knowledge about what kind of negative effects or risks that service

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6. CONCLUSION AND FURTHER RESEARCH

6.1 Conclusion

The main research question of this thesis is how to evaluate the performance of service modularity in elderly care from multiple perspectives. To answer this question, different validate measurement instruments were developed in this thesis. Specifically, along with the findings in works of notable authors such as De Blok et al (2010), Rahikka et al (2011), Pekkarinen and Ulkuniemi, (2008); Jacob et al, (2007), the possible effects of service modularity were related to four performance objectives, in terms of flexibility, quality of care, cost and responsiveness. Subsequently, theoretical performance indicators were derived from those objectives which in the end lead to four sub questions. To

answer the sub questions, a mixed method research was conducted. The design method gave guidelines on how instruments should be developed, while the case study not only strengthened the existence of the theoretical performance indicator but also gave rich empirical understandings of modular service in elderly care setting. Consequently,

instruments were developed on the basis of qualitative data and existing valid instruments in results section.

6.2 Theoretical and Managerial Implications

The findings of this thesis have several theoretical implications. First, the understanding of performance objectives in service modularity becomes more explicit. Second, this research contributes several questions and measurable items to evaluate the performance of service modularity. These questions are fine-tuned from existing measures of product modularity with the characteristic of healthcare service. Moreover, combining multiple stakeholders’ perspective in the development of measurement instruments gives a balanced view of the evaluation of service modularity performance. Further, the empirical evidences collected through case study confirm and strengthen the earlier findings in the works of De Blok et al (2010, 2012), Rahikka et al (2011) and Pekkarinen and Ulkuniemi (2008) to some extent.

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30 6.3 Limitations and Further Research

Several limitations to this research can be addressed. One of the limiting factors is that the interviews were only conducted with care provider and organization manager, which did not involve elderly patients. In this way, the richness of data was largely decreased by only interviewed with the organization manager and care provider. Second, since the pilot tests were not conducted in the selected organization, the reliability and validity of the developed instruments were decreased. Third, although different measurement

instruments were developed in present research, the effect of service modularity on performance was not empirical measured. Besides, the negative effects or risks of service modularity have not been explored yet. Further, the interpretation of data presented in a nested structure was not systematically investigated. Finally, instruments were

appropriate for those healthcare organizations that provide modular care to their patients. Hereby, the generalizability of these instruments was limited.

This research leaves rooms for further research. First, the pilot studies should be conducted with the focus group in the healthcare organization. Critical factors could be identified to further well-tuned these measurement tools as well as increase their

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35 APPENDIX A: Measurement Instrument for Evaluating the Performance of Service Modularity from Patient Perspective

This instrument is used to measure how service modularity influence performance from patient perspective. It contains several open-ended questions in relation with proposed performance indicators. This instrument is preferable used as an interview protocol to conduct case study with patients who experienced with modular service provision.

A. Questions to assess the effect of service modularity on flexibility Customization in service offering:

1. To what extent is your service offering flexible to cover all your requirements? 2. Can your service offering be customized by adding service modules as requested? 3. Are service modules flexible enough that can be combined in various ways to suit

your needs?

Personalization in service delivery:

1. How do the content of the service offering be altered into your specification during delivery process?

Client involvement:

1. How is the choice options of service module provided to you in modular supply? 2. Do you specify the features and choices of service module when developing your

own service offering?

3. When and how do care providers involve you in the service package configuration process?

4. Do you think your involvement in modular supply customize your service offering base on your own requirements?

B. Questions to assess the effect of service modularity on cycle time of service delivery

1. To what extent is your service offering delivered on time by means of service modularity?

EVALUATING THE MODULAR SUPPLY IN ELDERLY CARE FROM MULTIPLE PERSPECTIVES