CROSS-PLANT COORDINATION: EXPLORING ITS MECHANISMS AND EFFECTS

CROSS-PLANT COORDINATION:

EXPLORING ITS MECHANISMS

AND EFFECTS

Master Thesis

Author: Janek Kapahnke

Student number: 2751658

Supervisor: prof. dr. Dirk Pieter van Donk Co-Assessor: dr. Kirstin Scholten

Course: Master’s Thesis SCM

Course Code: EBM720B20 Date of submission: 22/06/2018

Words: 10.921

Abstract

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1. Introduction ... 4

2. Theoretical Background ... 5

2.1. Plant networks and their supply process ... 5

2.2. Cross-plant coordination ... 7

2.3. Coordination mechanisms ... 9

2.4. Conceptual model ...12

3. Methodology ...12

3.1. Research design & case selection ...12

3.2. Data collection...14

3.3. Data analysis ...16

4. Findings ...17

4.1. Coordination in the routine supply process ...17

4.1.1. Internal and cross-plant coordination ...17

4.1.2. External and cross-plant coordination ...19

4.2. Cross-plant coordination mechanisms ...22

5. Discussion ...25

5.1. Levels of coordination ...25

5.2. Construct of coordination mechanisms ...27

6. Conclusion ...30

6.1. Limitations & future Research ...30

6.2. Managerial implications ...31

7. References...33

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Name Page

Table 1: Operationalization of coordination mechanisms 11

Table 2: Overview of interview participants 14

Table 3: Overview of data collection 15

Table 4: Deviation in percent from contracted quantity 20

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Figure 1: Relations of a plant network 6

Figure 2: Levels of coordination 8

Figure 3: Conceptual model 12

Figure 4: Inventory development 20

Figure 5: Construct of coordination mechanisms 29

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Until 2003, IKEA experienced imbalances in their demand coverage, as some locations suffered under stock-outs while others ended up with obsolete inventories (Jonsson, Rudberg & Holmberg, 2013). This was caused by a decentralized planning concept across their network, where every region and store had a great deal of power and freedom about their order planning. IKEA solved this problem by introducing a centralized supply chain planning approach. However, centralizing operations is not always possible, as it might require certain prerequisites that otherwise create obstacles for the implementation such as functional products, vertical integration or one planning domain (Jonsson et al., 2013).

It has been found that firms need to disperse their plants all over the world to be able to compete globally (Canel & Khumawala, 2001), thus it is no surprise that the focus in manufacturing concepts also shifted from one plant to the whole network (Ferdows, 1989; Rudberg & Olhager, 2003; Cheng et al., 2015). Nevertheless, operational management of multinational plant networks is hardly investigated (Cheng et al., 2015; Ferdows, 2018). Hayes et al. (2005) stated that the design of multinational plant network is like designing any operating system, in that choices must be made not only regarding its configuration (size, location, scope, and specialization of the units belonging to the network), but also regarding its coordination (degree of centralization, policies, incentives, measures, and controls). Nevertheless, research has been mainly devoted to configuration (Pontrandolfo & Okogbaa, 1999; Colotla et al., 2003; Ferdows, 1989; Dubois et al., 1993; Meijboom & Vos, 1997).

5 coordination, the focus is laid on the supply process of a plant network. It has been revealed that external partners which are involved in physical and non-physical flows of plant networks, have a significant effect on operational performance (Cheng et al., 2016). Giving the complexity of such networks, this paper uses an in-depth case study approach (Eisenhardt & Graebner, 2007; Voss et al., 2002). Thus, this paper will investigate the following research question:

How to coordinate the supply process across plants in a plant network?

The remainder of the paper is organized as follows. First, a theoretical background about plant networks, cross-plant coordination and coordination mechanisms is established. Before analyzing the documentation as well as interview data, a method section is provided to introduce the design of the study and the background of the case. The results will be linked with the presented theory, to create a discussion which reveals valuable insights about the coordination of plant networks. In the last section, a well-founded conclusion is provided, incorporating limitations to this study as well as managerial implications.

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2.1.PLANT NETWORKS AND THEIR SUPPLY PROCESS

Nowadays, plant networks are not just delocalized production sites within given regions anymore but rather a system of complex relations (Yeung & Coe, 2015). This means, traditional manufacturing system boundaries are extended from a single plant to multiple plant level (Shi & Gregory, 2005). These networks are coordinated aggregations of intra-firm plants located in different places (Ferdows, 1989; Shi & Gregory, 1998; Rudberg & Olhager, 2003). The plants need to create aligned, synchronized and coordinated activities to create the best value possible (Meepetchdee & Shah, 2007).

6 similar products in multiple plants to increase flexibility and market proximity. In this setting, multiple plants may need to handle similar suppliers to acquire the same raw materials. Therefore, multiple plants have similar processes in place to deal with the suppliers, which confronts them with the complexity of cross-plant coordination (Prasad & Babbar, 2000; Colotla et al., 2003). The supply process is defined through multiple sub-processes such as negotiating, planning, ordering and the supply. Multiple plants as well as the headquarters can be involved with one single supplier. The described setting is displayed in figure 1 to illustrate such a network.

Figure 1: Relations of a plant network

7 To overcome this challenge, centralization has been introduced as being beneficial through, for instance, improved transparency, visibility and synchronized processes (Dreyer et al., 2009). Jonsson et al. (2013) summarized that centralization mainly concerns common and standardized processes and working methods, a centralized organization, as well as an integrated information technology (IT) infrastructure. Furthermore, a centralized supply process requires well-established communication lines between departments to avoid inefficiencies like maverick buying (Monczka et al., 2009). Nevertheless, centralization also raises the issue of balancing responsibilities between the different entities and the headquarters (Hayes et al., 2005; Netland & Aspelund, 2014). A single decision maker is required to optimize the network with the union of information that the various decision makers have (Anupindi & Bassok, 1999). However, it has been found that the multiple decision makers are acting in their own best interests, assuming that all of the other actors will do the same (Lee & Kim, 2002). The incongruence of objectives may result in a fragmented structure (Pibernik & Sucky, 2006; Lorentz et al., 2012) ultimately leading to rejection by individual entities or system-wide inefficiencies (Pibernik & Sucky, 2006). Hence, supply chain planning decisions are most commonly coordinated on a decentralized basis (Pibernik & Sucky, 2006). Further, Benton (2007) suggests that most companies seem to practice some combination of centralized and decentralized approached in purchasing. This research focuses on a plant network implementing a decentralized approach which may require coordination across plants to avoid the introduced inefficiencies.

2.2.CROSS-PLANT COORDINATION

Coordination, which is defined as one of the key dimensions characterizing supply chain management (Christopher, 1992; Stock et al. 1998), is important in every business environment and it may facilitate information sharing or incentive alignment (Arshinder et al., 2008; Lehoux et al., 2014). Coordination refers to the pattern of interactions, decision-making and communication that takes place amongst the organizations involved (Romano, 2003). Full coordination is defined by Sahin and Robinson (2002, p. 507) as “all decisions are aligned to accomplish global system objectives and that is what every network should strive for”.

8 Linking activities may be the solution to overcome the challenge of developing mechanisms that create, develop and share processes of multiple plants (Crespo et al., 2014; Fey & Furu, 2008).

Coordination between plants cannot be allocated in the traditional dimension of coordination such as internal plant coordination (within) or external plant-supplier coordination, but rather be determined as a mixture of both. The different levels are illustrated in figure 2. Interrelations between the internal and external sphere may be assumed, as in single organization underdeveloped internal coordination may prevent external from fully impacting performance (Germain & Iyer, 2006). Its argued that a firm showing high internal coordination will be more capable of achieving a high level of external coordination due to the ability of recognizing the value of new information (Cohen & Levinthal, 1990). Reflecting on both dimensions, cross-plant coordination is rather allocated between both dimensions.

Figure 2: Levels of coordination

9 positive effect on firm performance. They further investigated the relationship of integration and the well-known operational performance measures of costs, quality, delivery, innovation and flexibility. A positive and significant aggregated correlation was found. However, individually only innovation and delivery revealed positive significant results. To align these findings with this study, operational performance is understood as a holistic concept with focusing on costs, delivery and flexibility which are deemed particularly important in the supply process.

2.3.COORDINATION MECHANISMS

Due to the novelty of cross-plant coordination, the introduced coordination mechanisms are extracted from literature elaborating on coordination. Coordination measures in general create a pattern of interactions, decision-making and communication that takes place amongst the organizations involved (Romano, 2003). Moreover, they are required to answer the question of how to link or integrate with other plants (Pontrandolfo & Okogbaa, 1999). Multiple studies considering various coordination mechanisms have been reviewed (Romano, 2003; Arshinder et al., 2008; Cheng et al., 2016; Danesea et al., 2004). Information sharing, joint

decision-making, liaison devices and information technology are determined as the most valuable to this

study.

Information sharing is one of the most discussed coordination mechanisms in the literature (Romano, 2003; Grandori & Soda, 1995; Arshinder et al., 2008; Cheng et al., 2016; Rudberg & Olhager, 2003). It may be seen as the key requirement and foundation of supply chain coordination (Sheu, Yen & Chae, 2006; Willem et al., 2006). Sahin and Robinson (2002) supported this with their findings that a lack of coordination occurs when decision makers have incomplete information, which amplifies the requirement for information sharing across a plant network. Romano (2003) argued that extended visibility on processes, information and resources over the whole network is a coordination mechanism. However, information sharing among network partners may be interpreted as an antecedent of them. Nevertheless, in many cases information sharing alone does not improve performance, as also physical flows among partners might be required (Sahin & Robinson 2002; 2005). Devaraj et al. (2007) and Kulp et al. (2004) found that information sharing is necessary to understand the supply chain. Nevertheless, information sharing cannot enhance the competitiveness of the supply chain if the members lack the means to coordinate their planning.

10 Additionally, it used to mitigate future uncertainty (Arshinder et al., 2008) to ultimately create an integrated and collaborative network (Mudambi & Navarra, 2004). Joint decision-making is defined as the process of coherent decision-making where network participants align their decisions in planning and operations (Arshinder et al., 2008). If it is not in place, plants may act in their own best interest, as they might assume that others do the same (Lee & Kim, 2002). Joint decision-making is related to information sharing, as incomplete information might result in plants making decisions pursuing their own individuals goal instead of acting in the best interest of the network (Narayanan & Raman, 2004). From an information processing view, joint decision-making prevents an upward referral and unloads the hierarchy (Galbraith, 1974). Therefore, Galbraith (1974) suggests to employ selectively joint decision processes which cut across lines of authority.

Moreover, based on the information processing model of Galbraith (1974), liaison devices as well as IT can be defined as a structural mean to coordinate a process. Galbraith (1974) suggests that both integrating mechanisms may support coordination through a structural increase of the information processing capabilities. Therefore, both can be seen as an antecedent to achieve information sharing or to align decision-making. It is highlighted that these mechanisms are useful to facilitate information sharing especially if decision makers are exchanging an increasing amount of information. It is indicated that a design problem may be found when decision makers cannot communicate with all interdependent roles.

11 IT has been defined as an enhancing coordination mechanism (Arshinder et al, 2008; Clemmons & Simon, 2001; Frohlich, 2002; Sanders, 2008). IT makes real time information facilitating management and control of activities possible (Cannella et al., 2014) while simultaneously decreasing the cost of coordination as well as the transaction risks (Finnegan & Longaigh, 2002; Malone & Crowston, 1994; Sanders, 2008). Hence, an effective IT connection improves the integration between supply chain partners in terms of material flows (Soliman & Youssef, 2001). In general, it facilitates the information sharing and increases the capability in volume and complexity of information which needs to be communicated with other entities (Prajogo & Olhager, 2012). Additionally, it supports decision makers by structuring the information (Galbraith, 1974). In line with that, IT also enhances joint decision-making as it provides the managers of a firm as well as its partners with a comprehensive picture of situations and helps them to make appropriate decisions (Fawcett et al., 1996). An example is the provision of real-time information, such as inventory levels, which may facilitate the alignment of operations between firms and suppliers (Paulraj & Chen, 2007). Table 1 provides an overview of the operationalizations for the introduced coordination mechanisms.

Coordination Mechanisms Operational definition

Information sharing

The sharing of information regarding demand, inventory levels, orders, point of sale data etc. in a timely manner whereby the input can support partners with regard to anticipating future events (Arshinder et al., 2008).

Joint decision-making

Coherent decision-making among the subsidiaries aimed at mitigating future uncertainty to optimize supply chain benefits (Arshinder et al., 2008)

Liaison device

Liaison devices are jobs created to directly coordinate the work of two units without having to pass through

managerial channels. These positions may or may not carry formal authority per se. (Mintzberg, 1979). It may be understood as a coordinator within the network.

Information technology

Application of IT to improve intra-organizational

coordination via means such as electronic data interchange (EDI), enterprise resource planning (ERP) systems and many more to rapidly exchange information to optimize SC operations (Arshinder et al., 2008).

12 2.4.CONCEPTUAL MODEL

The established theoretical background highlights the importance of coordination. To extend current literature, this study analyzes coordination in a new context of a plant networks supply process. To answer the question how to coordinate the supply process across plants in a plant network, this research focuses firstly on exploring cross-plant coordination in the construct of internal and external coordination. Secondly, it focuses on understanding cross-plant coordination in the supply process by examining four coordination mechanisms. Especially, the relation of cross-plant coordination and external coordination is of particular interest, as it has been revealed that suppliers have a significant effect on operational performance (Cheng et al., 2016). Figure 3 summarizes these two aims of the study in one model.

Figure 3: Conceptual model

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3.1.RESEARCH DESIGN & CASE SELECTION

13 which preserves the chance to generate and refine theory (Benbasat et al., 1987; Voss et al., 2002; Ketokivi & Choi, 2014). Moreover, the aim is to answer a “how” research question which creates the opportunity to study the plant relations with a relatively full understanding of the nature and complexity (Benbasat et al., 1987). The explorative approach grants the chance to shine light on the black box of cross-plant coordination. Even though research has progressed about theoretical developments of coordination in itself, academia fails to transfer and confirm these findings into the niche between internal and external coordination of plants.

14 3.2.DATA COLLECTION

In accordance with the retrospective case selection, this study relies as main source of information on 8 semi-structured interviews (Eisenhardt & Graebner, 2007). In order to cover multiple perspectives, three plants including two respondents respectively as well as two supplier representatives have been interviewed. An overview is provided in table 2.

Entity Plant location Interviewees Position Length of interview

Type of interview

Label in analysis

1 Netherlands Purchaser 40 min

Face-to-face NET-LOG-NL 2 Netherlands Group leader logistics 48 min

Face-to-face NET-PUR-NL

3 France Purchaser 40 min Skype NETLOG

-FRA 4 France Logistics employee 53 min Skype NET-PUR-FRA 5 Turkey Purchaser 50 min Skype NET-LOG-TUR 6 Turkey Material planner

logistics 55 min Skype NET-PUR-TUR

Supplier

location Interviewees Position

Length of interview

Type of interview

7 Italy Commercial manager 1h 8 min Skype SUP-ITA 8 Turkey Key account manager 56 min Skype SUP-TUR

Table 2: Overview of interview participants

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Data type Description Purpose Date

Meetings off- record

Meeting with group leader logistics

Introduction to the company and its processes

February 2018 Kick-off meeting with

project management production networks

Introduction to the company and its processes

February 2018 Weekly meetings with

project management production networks

Discuss progress and ensure feasibility of project such as contact

persons

February – June 2018 Meeting with plant

management

Discussion of preliminary results and definition of appropriate

interview partners

April 2018

Observations

Weekly presence at

production site Get insights to daily operations

February – June 2018 Production line tour

appliance Company introduction

February 2018

Documents

Material Planning of the purchasing

Comparison planned products with actual ordered quantities ERP extract of inventory

status for the 2 suppliers

Comparison of inventory levels per plant

ERP extract of invoiced goods for 2 suppliers

Definition of relevant components for off record discussions ERP extract of material

movements goods for 2 suppliers

Comparison of inventory levels per plant

Table 3: Overview of data collection

16 network and higher degree of information richness. The semi-structured interview guides use a funnel approach which firstly includes general and later more specific and detailed questions (Voss et al., 2002). The information gathered in the preparation phased have been linked with the established theoretical background to create questions that reveal a full understanding of the relationships of the parties involved. The interview guides offer the opportunity to validate the respondent’s answer by ensuring that all respondents are replying to the same questions as differences in responses are due to differences among the respondents’ (Gordon, 1975; Bailey, 1987).

During the interviews, respondents were encouraged to describe the actual process in place to determine what happens and, furthermore, provide specific examples in order to avoid memory bias (Schacter, 1999). The selected entities were approached via phone and e-mail. All interviews have been recorded to ensure objective data. The interviews were held either face-to-face or via Skype. It is acknowledged that telephone interviews are not a practical alternative to face-to-face interviews, as they might lose subtleties associated with physical interaction (Sturges & Hanrahan, 2004). However, Holt (2010) found ideological, methodological and practical benefits of using telephone interviews. He suggests it allows the researcher to focus on the text and avoid imposing contextual information on the data. The transcripts were sent to the respondents to confirm, converge and clarify their answers (Yin, 2009). The follow-up contact was conducted via e-mail and telephone.

3.3.DATA ANALYSIS

The data analysis follows the three-step approach of Miles and Huberman (1994): data reduction, data display and conclusion drawing and verification. The data analysis phase is carried out simultaneously with the data collection phase to create the opportunity of gathering flexible data and making adjustments to the study (Eisenhardt, 1989), which is demonstrated by the adjustments of the suppliers’ interview guide. This highlights the iterative process of case studies where interviews, the literature background and the analysis are under constant progression (Mason & Leek, 2008).

17 codes already indicating relations of multiple mechanisms which are displayed in appendix 5 and 6. Due to the explorative nature, in-depth qualitative data is collected which is required to ultimately contribute to answer the research question. Therefore, the focus lies on analytical generalization towards theoretical concepts rather than statistical generalization (Jüttner & Maklan, 2011). The data provided by the suppliers is used to triangulate and contrast the findings across plants. In the next section, the findings among the respondents are outlined and variations as well as communalities are highlighted. Statements made by the respondents are presented to underline certain findings. The origin of the quotes can be determined by the labels provided in table 2.

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The analysis of the data unraveled specific details on how to coordinate a plant networks supply process. Particularly, how coordination in form of information-sharing, joint decision-making, liaison devices and IT is structured within a network. Furthermore, the introduced levels of coordination have been clearly detected within the data. Unsurprisingly, it has been found that cross-plant coordination has indeed an effect on operational performance. Moreover, it has been found that cross-plant coordination and centralization face similar issues in terms of goal incongruence. The analysis starts with the presentation of internal, external and cross-plant coordination. Subsequently, the coordination mechanisms of cross-plant coordination are examined. As cross-plant coordination is mostly implemented in cases of problems in the supply process, the modified process is investigated.

4.1.COORDINATION IN THE ROUTINE SUPPLY PROCESS

4.1.1.INTERNAL AND CROSS-PLANT COORDINATION

18 on mutual IT-systems such as the enterprise resource planning system. No liaison device is found in the internal plant process.

Cross-plant coordination is perceived by all plants as unnecessary for the routine supply process. This type of process is arranged internally and the underlying reason for that is that it simply does not require interaction with other plants. Nevertheless, cross-plant coordination is increased with arising problems in the supply process. The quote below reflects what all plants have indicated:

“The normal supply process is not coordinated with other plants at all. In the normal operations it is a local thing. We just contact the other plants if we have problems.” (NET-LOG-NL)

Even though the overall use of coordination mechanisms to coordinate the process is regarded as low, the mechanisms can still be detected. Low information sharing influences the decision-making process in the sense that it does not allow joint decision-making, as plants are unaware of decisions taken by other plants. Little evidence was found about the implementation of joint decision-making, which is supported by the findings made at the suppliers’ side. The logistics planner from the Netherlands underlines the differences across plants in the following quote:

“Information, such as lead times or incoterms are plant specific. Only the part number and the specification of the part numbers are for all plants the same. So, after we got in contact with the supplier, the logistics department creates the logistics agreement. This information is not shared with

other plants.” (NET-LOG-NL)

A liaison device is in place for certain component groups in the form of a centralized purchasing function. The liaison device gathers information and arranges contracts with suppliers. There is a dissension across plans what the actual task of the central function is. As the quote below highlights, the plants described the main task rather as information gathering and facilitation of decision-making.

“We have the central purchaser and the central department of the network which organizes all the suppliers within the network. This department gives information to all the plants.” (NET-LOG-FRA)

The focus on internal coordination and the low level of cross-plant coordination let the individual plants appear as different entities without a relation to the manufacturing network. This is indicated by the suppliers.

“We see the plants as separate units not as a unique entity. We know what each plant belongs to focal company but we see it as each plant as a different customer.” (SUP-ITA)

19 coordination in the supply process while cross-plant coordination is rather regarded as a burden to processes.

4.1.2.EXTERNAL AND CROSS-PLANT COORDINATION

In contrast, the external side indicates that cross-plant coordination is required to make the supply process more effective. First of all, the suppliers highlighted the interrelatedness of plants in the production network. Since components are sourced from a single supplier but demanded by multiple locations, plants are required to arrange the process beforehand to increase efficiency at the suppliers’ side. Additionally, suppliers have a limited capacity which requires the plants to coordinate their demands between each other. The supplier from Turkey gave an explanation of how delivery processes of the multiple plants are interrelated:

“The problem we face with the whole network is that half of the cable are needed in Turkey. When this half is not manageable, the other half is also not manageable. Because both plants use the same

production base and the same raw materials.” (SUP-TUR)

Moreover, the uncoordinated process affects the plant-supplier relationship. The suppliers indicate that their performance is reduced through unaligned decisions by the supplied plant network. The suppliers coherently mentioned two examples, where missing joint decision-making causes lower delivery performance and a decrease in flexibility. The quote of the supplier from Italy represents the suppliers’ stance on the different logistics requirements: “A common lot size in the package would also make us more flexible. It would make our life’s easier

because we have to prepare the pallets and each plant has different request. One requirement is the way we pack and prepare the pallets. Each pallet is different because you have different trucks going

to the different plants. Some are a little bit higher some are a little bit lower, so you cannot store the pallets in the truck correctly. if we had the same characteristics, we could work in a standardized way

also on our side and we could save time and avoid mistakes.” (SUP-ITA)

Another example given by the suppliers are unaligned order dates, which cause problems on the supply side. Thus, defining a common order date would create greater flexibility for the supplier and ensure greater delivery performance. The Turkish supplier summarized the current situation and indicates how aligned decision-making would improve their situation.

“We receive orders from Turkey every day and from Germany not every day. From Turkey sometimes even twice a day. It would help immensely to implement a common order date. If we get the orders all

on the same day, we could have an easier life.” (SUP-TUR)

20 the component is also required at another plant of their network. In this situation, the Dutch plant modified their production schedule to not run out of stock.

Figure 4: Inventory development

Furthermore, plants claimed that they were confronted with situations where no information about certain decisions has been shared. For example, table 4 indicates the percentage of the actual order quantity of three components compared to the contracted order quantity by the liaison device.

Table 4: Deviation in percent from contracted quantity

Plants were unaware of these tremendous differences and kept their standard order process with the supplier in place. This ultimately lead to enormous delivery problems. The particular situation has been described by the logistics planner from the Netherlands.

“We don't have enough contact with our plants to get the information to solve the issue. I also do not have the ability to see which plants are affected. I don’t even know to which plants the supplier

actually delivers.” (NET-LOG-NL)

As indicated, in case of problems during the supply process cross-plant coordination has proven to be helpful in solving issues and maintaining delivery performance. This underlines the relationship of cross-plant coordination and operational performance in the supply process,

0 PC 500 PC 1.000 PC 1.500 PC 2.000 PC 2.500 PC Janua ry-17 Febr uary -17 Marc h-17 Apr il-17 M ay-17 June -17 Ju ly-17 Augu st-17 Septe mbe r-17 Octobe r-17 Nove mbe r-17 Dece mbe r-17 Da ily S to ck L ev el

Inventory development of a component required in the

Netherlands and Germany

Daily Stock Level in the Netherlands Daily Stock Level in Germany

Product Contracted Quantity Actual order quantity Difference in units

Deviation in percent from contracted quantity

Component A 6.530 24.437 17.907 274,23%

Component B 6.368 26.726 20.358 319,69%

21 as increased cross-plant coordination ensures delivery performance of the supplier. The elaboration on the mechanisms in the next section will further investigate this underlying principle.

It has been mentioned that the effective implementation of a common IT system depends on the alignment of decision-making. Hence, it can be concluded that the fundamental basis to create a coordinated supply processes is joint-decision making. This finding is highlighted by the supplier from Italy:

“Even if we would have EDI for all the plants (to prevent supply problems), each plant sends out their own needs on a different defined day. Every plant sends it based on their own planning. The UK sends it on Tuesday, the Netherlands on Wednesday and Germany on Thursday. In general, I would be

better to get the orders all on the same day but each plant is working on its own.” (SUP-ITA) IT is used to share information across-plants, besides no further utilization as network coordinator mechanism is detected. It rather facilitates information sharing and therefore, if done, joint decision-making. The supplier in Italy stated that information exchange is partly done through the use of IT. Nevertheless, plants do not use a common way to communicate this information, supporting the little amount of joint decision-making in place.

“We have a weekly overview from the plants. On a weekly basis each plant is sending out their demands. The way they transmit this differs. There are some plants which are connected via EDI.”

(SUP-ITA)

In case of supply issues, plants need to align decision-making about the division of available components. However, as long as the process remains uncoordinated, the supplier from Italy indicates that quantities are assigned on a first-order first-serve basis. This causes additional workload for the suppliers and the plants, as either one plant requiring the component does not receive it or the supplier has to arrange cross-plant coordinative actions.

“In case of troubles the priorities are made based on the arrival date, so who was ordering earlier. In accordance with the agreement, that one has the priority. In case of troubles, where the same product is used for different plants, we notify the network. We and try to find out together with the plants who

could use the component and if this component is used on several products. Maybe they can change their production schedule so that the other plant could get the component.” (SUP-ITA)

In these situation, plants create information requests individually, which result in an information overload for the suppliers, which makes it difficult for them to keep an overview of their supply process ultimately leading to lower delivery performance. However, the plants request these information, as they act in their own interest. As mentioned by the logistics planner from France, they want to ensure their individual production and therefore they constantly push suppliers for information and components.

22 deliver. If I only send them the normal schedule, they won’t deliver the products to me.”

(NET-LOG-FRA)

In this context, the supplier from Turkey mentioned a liaison device as potential remedy, as a centralized point of contact would largely reduce the amount of information exchanged.

“I would like to have only one contact I have to talk to. Then I don’t have to explain to everyone the same thing. I lose a lot of time through this and it becomes a very hard job.” (SUP-TUR)

In general, the suppliers regard the liaison device as much more important than the plants. They would support a more intense inclusion of the device to optimize information sharing and decision-making. They characterize the liaison device as being a facilitator to exchange information and align decisions. Even though information sharing across plants is found to be low in the routine supply process, the plants regard information sharing as useful. For instance, knowledge about logistics requirements or order quantities.

To conclude, coordination is found on all three levels in the case. The network focuses on internal coordination in case of routine processes and increases cross-plant coordination with increasing problems in the supply process. Internal coordination is defined as the basis to arrange the supply process. The level of external coordination is currently governed through the individual plant arrangement. Even though plants do not consider cross-plant coordination as necessary, the low level of coordination clearly causes a reduction in performance in the supply process. In particular, unaligned decision-making causes a reduction in delivery performance and flexibility. Additionally, inaccessible or missing information causes issues in the supply process. The act in self-interest by the plants hampers aligned decision making and makes suppliers suffer under an information overload when plants approach them individually. In line with this finding is that a higher level of cross-plant coordination improves supplier performance. The following section will focus on the individual coordination mechanisms to create an understanding of how cross-plant coordination may be implemented in the supply process.

4.2.CROSS-PLANT COORDINATION MECHANISMS

23 routine tasks are designed to handle processes which are not exposed to abnormalities. The relation between the individual mechanisms can be already found in the routine process. Nevertheless, in case of increased implementation the relations become clearer. In the previous section, various problems in the supply process are introduced. The logistic planner from France gave an example of a situation where cross-plant coordination is triggered:

“When everything is going fine, we work for ourselves. However, if there is a problem, it is coordinated with other plants. This really depends on the problem. When a delay is caused by the forwarder, I don’t need to coordinate it with other plants. But when it is a capacity problem of the supplier, I need to communicate to every plant, as we need to know how to divide the quantities.”

(NET-LOG-FRA)

Plants and suppliers indicate that cross-plant coordination is used to overcome the issues of incomplete or missing information as well as unaligned decision-making. Liaison devices, such as centralized purchaser or a logistic department, facilitate cross-plant information sharing and joint decision-making. In particular, information is gathered from all the plants and accumulated to create an overview. This information is redistributed to the plants and ultimately a joint decision is made. It has been learnt that the current process requires capacity issues to become large enough to be raised to the liaison device.

“Only if the issues get as big the problems we had with Supplier A or Supplier B in the past, the whole network becomes involved. At a certain moment where I can see that other plants are also struggling with the same problem and I can see that we are not able to solve the problem anymore and we raise the issue to central logistics coordinator. He needs to take over then and make the decision for the

whole network.” (NET-LOG-NL)

In contrast, suppliers demand a liaison as single point of contact to improve efficiency of the information sharing process between them and the network. Moreover, suppliers name the liaison as indispensable for crisis situations where decision-making needs to be fast. The liaison device mitigates the problem of plants acting in their best interest. The plants agree on that and state that it is easier in these situations to shift responsibility to the liaison device who basically applies centralized decision-making. The Italian supplier underlines the problem-solving characteristic of the liaison device in the following statement:

“The central person makes things easier for us because every plant sees only their own reality. So, for everybody it is always urgent but we don’t know how urgent, so we are actually blind. Then we can

24 supplier from Turkey mentions time inefficiency as main reason why the liaison device cannot handle every issue:

“I cannot escalate every problem to the central purchasing. (…) I don’t have the time to escalate all these problems and you cannot solve them all.” (SUP-TUR)

As indicated information sharing is largely influenced by the facilitation of the liaison device, however plants may also communicate directly with each other to solve issues and to align decision-making. To share information, the network relies heavily on the usage of IT. Information are uploaded, such as individual demands, to be accessible by the liaison device or other plants.

“The information is shared via a common excel sheet showing our demands and exact stock levels. It is extracted from the ERP system and we just share the quantity according to the shortages we face.

The excel sheet is on a common platform in the Portal.” (NET-LOG-TUR)

Even though cross-plant coordination is detected in the data, multiple obstructions to effectively implement it are named by the plants and the suppliers. These can be summarized in inaccessible or incomprehensive information, act in self-interest as well as missing standards to handle the supply process.

In respect to information sharing, some plants indicate that they do not possess the means to access all relevant information. The others state that they may access the information but could not use it instantly due to individual difference across plant. Therefore, the required modification of information indicates missing standards across plants. Moreover, this highlights the crucial role of IT, as only plants with a different IT system than the majority could not access the relevant information. The liaison device helps these plants to get the required information.

“We don't have enough abilities to see what quantities other plant ordered. It is not easily accessible. We have the possibilities but not all plants have the same system. Currently, we just call the central

logistics and ask if other plants also face similar issues.” (NET-LOG-FRA)

It is concluded that plants are acting in self-interest. Pursuing their own instead of the network goals is a major impediment of effective cross-plant coordination. In the example of internal competition between the German and the Dutch plants, they focus on their own production pursuing the ultimate goal of maintaining performance. The logistics planner from Turkey summarized their local mindset using the following words:

“For every planner in every plant, the first goal is to not let their own production stop. This is very clear because I am working in Turkey and the other is working, for example, in the Netherland. Of course, everyone focuses on not letting their own production stop. Nevertheless, if a long-lasting problem comes up, we warn each other and try to find a common way to, for example, allocate the

25 Again, plants referred to a liaison device as a remedy to overcome self-centered decision making, as the liaison device focuses on the network objective in his decisions rather than on the needs of the individual plants.

To conclude, coordination across plants is a complicated endeavor especially in the supply process, as it involves additional entities such as suppliers. Joint decision-making, as one of the main drivers causing delivery problems, is found to likewise improve performance. In general, at the end of a problem-solving process, the outcome is a joint decision. Moreover, information sharing is a essential to coordinate the process and to achieve joint decision-making. A liaison device is named by plants and suppliers as facilitator of information sharing and joint making. In case of severe problems, the liaison device centralizes decision-making to be able to respond quickly. IT is mainly used as a foundation to share information. In the following part, literature is used to reflect on the findings and to ultimately come up with propositions as well as a model describing the construct of coordination mechanisms.

5.

D

The aim of this research is to explore the concept of coordination in the context of a plants network supply process. Thus, this paper contributes to the understanding of plant networks and its horizontal relations. Cross-plant coordination has been allocated between the dimensions of internal and external coordination. Moreover, the exploration of cross-plant coordination itself has revealed details about its underlying process. In the following section, starts by discussion the general findings about cross-plant coordination in the context of coordination are reviewed by reflecting on current literature. Subsequently, the defined mechanisms of cross-plant coordination are scrutinized under the lens of academia.

5.1.LEVELS OF COORDINATION

26 Ketokivi and Schroeder (2004) that the link between coordinative practices and quality is relatively weak.

These insights allow another interesting conclusion about the levels of coordination. The data indicate that external coordination requires a plant network to first coordinate internally and across plants to improve performance of an external entity. This extends the conclusion of Cohen and Levinthal (1990, p. 128) which found that a firm showing high internal coordination will be more capable of achieving a high level of external coordination. In plant network context, it is found that not just internal plant coordination needs to be implemented but also cross-plant coordination needs to be in place. This is also in line with Germain and Iyer’s (2006) findings for single organizations that underdeveloped internal coordination prevents external from fully impacting performance. Overall, the literature on individual firms and the findings lead to the conclusion that a low level of cross-plant supply results in problems on the external side. These findings are summarized in the following proposition:

1. Cross-plant coordination is an antecedent to achieve effective external coordination

Moreover, plants unanimously indicated that they desire to pursue their own objectives instead of the network perspectives. In the case, this keeps the plants from implementing aligned, synchronized and coordinated activities to create the best value possible for the whole organization (Meepetchdee & Shah, 2007; Sahin & Robinson, 2002, p. 507; Gupta & Weerawat, 2006). The phenomena of acting in own interest is a similar impediment to effective implementation in centralized structures (Pibernik & Sucky, 2006; Lorentz, et al., 2012, Lee & Kim, 2002). Besides, the outcomes of a fragmented structure (Pibernik & Sucky, 2006; Lorentz, et al., 2012) are also found in the case as the plant network is viewed as multiple entities from the outside parties. Additionally, also system-wide inefficiencies are detected in the case (Pibernik & Sucky, 2006; Lorentz et al., 2012, Lee & Kim, 2002). Since plants suffer under the same impediments and performance outcomes as organizations implementing a centralized structure, it is concluded that cross-plant coordination can centralize a network without deliberately implementing it. This finding leads to the proposition:

2. Low cross-plant coordination and false implementation of centralization face similar impediments and performance outcomes

27 strategies (Zhang, Dadkhah & Ekwall, 2011). Moreover, cross-plant coordination also facilitates visibility which is another reactive strategy, for instance, sharing production schedules across plants (Zhang, Dadkhah & Ekwall, 2011). The created flexibility enables the network to deal with faced levels of uncertainty (Manuj & Mentzer, 2008; Scholten et al., 2014). However, the findings indicate that a lack of cross-plant coordination may cause delivery problems. Therefore, it could rather be implemented as proactive resilience strategy to prevent the problems in the first place. Hence, the network would erroneously implement a proactive strategy as reactive one, meaning that it uses a method preventing the problem as strategy to resolve it. Based on these findings, it is proposed that:

3. Cross-plant coordination can be implemented as a proactive resilience strategy

Summarizing the propositions of cross-plant coordination, it is found that cross-plant coordination is an antecedent to effective external coordination. Additionally, a relation between centralization and cross-plant coordination is discovered. Lastly, cross-plant coordination in the context of resilience is discussed.

5.2.CONSTRUCT OF COORDINATION MECHANISMS

28 easy interchange of data which increase the capability of communicating larger volumes and complexity of information (Prajogo & Olhager, 2012). Different IT systems are determined as a reason why information cannot be exchanged. Hence, a common IT is regarded as the fundamental basis to share information across plant and can be therefore defined as an antecedent of information sharing. These insights lead to the following proposition:

4. IT is an antecedent of information sharing which is an essential mechanism to coordinate a plant network

The findings reveal that especially the supplier side claims inconsistent decision-making across plants as main driver for problems. Unaligned decisions, for example the various logistics requirements, deviate from the plant objective of achieving an aligned process (Mudambi & Navarra, 2004; Arshinder et al., 2008; Cao et al., 2010). Therefore, plants face uncertainty that results in delivery problems. The findings match with Arshinder et al. (2008) who define joint decision-making as coping mechanisms of uncertainty. Multiple plants have indicated missing standards in combination with missing allocation of responsibilities leading to unaligned decisions in planning and operations (Arshinder et al., 2008; Cao et al., 2010). Joint decisions are usually made based on information shared via the IT system. The IT system provides a comprehensive picture of situations and, thus, helps to make appropriate decisions (Fawcett et al., 1996). Based on the findings following proposition is made:

5. Information sharing is an antecedent for an effective implementation of joint decision-making

29 way of communicating them (Galbraith, 1974; Gupta & Govindarajan, 1991). It needs to be noted that plants fall back on it mainly in cases of critical problems which indicates that it is used as a reactive resilience device. Even though centralization is associated with improved transparency, visibility and synchronized processes (Dreyer et al., 2009), individual goal seeking prevents the liaison device from full utilization. Shifting to a more centralized structure with greater formal authority could improve that. Reflecting on the discussion the following is proposed:

6. Liaison devices facilitate information sharing as well as joint decision-making and are implementable as reactive resilience device

The discussion of coordination mechanisms is concluded in the model of figure 5. It provides an overview of the interrelations of the different coordination mechanisms. Overall, it has been found that all named coordination mechanisms are used to coordinate across plants. No mechanisms have revealed stand-alone characteristics, meaning that all mechanisms are interrelated. IT is the basis to share information. Information sharing in general facilitates joint-decision making. Nevertheless, it may be also used to just share information across plants. Moreover, a liaison device is either used to share information or facilitate information sharing across plants. It facilitates joint decision-making or even centralizes the decision-making process.

30

6.

C

The findings of the paper contribute to the literature of plant networks integration and in particular coordination. During the single case study, the question of how to coordinate a plant networks supply process has been investigated. The relation of cross-plant, internal and external coordination is investigated. The findings extend current literature by indicating an antecedent relationship of cross-plant coordination and external coordination. Internal coordination is defined as the fundamental basis to arrange the supply process. Even though the representatives of the plants regard cross-plant coordination as unnecessary, the findings indicate a positive relationship with operational performance. Missing cross-plant coordination resulted in performance issues while increasing cross-plant coordination ensured delivery performance. On one hand, it is demonstrated how unaligned decisions or missing information hamper performance and, on the other hand, how joint decision making and liaison devices ensure delivery performance.

Additionally, cross-plant coordination may be seen as a bridge between a decentralization and centralization. It allows decentralized networks to gain the advantages of a centralized network without implementing a full centralized structure. Nevertheless, similar impediments and performance outcomes are found in case of false implementation. Problems in the supply process resulted in increasing cross-plant coordination leading to the conclusion that it can be implemented as resilience strategy. The individual coordination mechanisms are examined and cross-relations are shown. The construct highlights the interrelation across the mechanisms, indicates antecedent relationship and stress the facilitating characteristics.

6.1.LIMITATIONS & FUTURE RESEARCH

31 is biased, since the resource constraints allowed just one researcher to gather and evaluate the data.

This paper may be used as basis and indications for future studies. After exploring the concept of cross-plant coordination, future studies may focus on validating the findings. Especially, a quantitative study may confirm the findings by including all three levels of coordination and multiple industry sections as well as network sizes. Particularly, the findings about cross-plant coordination and its relationship with external parties may offer great potential for future studies. As indicated in the discussion, cross-plant coordination is used as a resilience strategy, thus it is suggested to evaluate cross-plant coordination in this specific context. Further elaboration is required to exactly determine the proactive and reactive nature. The interesting relation of the characteristics of cross-plant coordination and centralization has been highlighted, thus academia may use these insights to further explore the relation and understand the distinctions between decentralize networks implementing cross-plant coordination and centralized networks. The study assigns a beneficial role to liaison devices. Recent literature lacks evaluation on this concept. Therefore, future studies could isolate this coordination mechanisms in the context of manufacturing networks and explore the implementation of such devices. To put it in a nutshell, the study reveals certain limitations in respect of generalizability particularly due to the research design. However, the explorative nature allows interesting conclusions and provides a basis for future studies.

6.2.MANAGERIAL IMPLICATIONS

32 individual coordination mechanisms as differently important. Suppliers rather favor a more centralized structure through a liaison device and plants value their independence and focus on information sharing.

33

7.

R

Anupindi, R., & Bassok, Y. (1999). Supply contracts with quantity commitments and

stochastic demand. In Quantitative Models for Supply Chain Management. S. Tayur, R. Ganeshan and M. Magazine (Eds.) Quantitative Models for Supply Chain Management, Boston, Dordrecht, London, pp.197–232.

Arshinder, Kanda, A., & Deshmukh, S. G. (2008). Supply chain coordination: Perspectives, empirical studies and research directions. International Journal of Production

Economics,115(2), 316-335.

Bailey K.D. (1987) Methods of Social Research. The Free Press, New York.

Benbasat, I., Goldstein, D. K., & Mead, M. (1987). The Case Research Strategy in Studies of Information Systems. MIS Quarterly, 11(3), 369.

Benton, W.C. (2007). Purchasing and Supply Chain Management. McGraw-Hill, Irwin, Boston.

Canel, C., & Khumawala, B. M. (2001). International facilities location: A heuristic

procedure for the dynamic uncapacitated problem. International Journal of Production

Research, 39(17), 3975–4000.

Cannella, S., Framinan, J. M., & Barbosa-Póvoa, A. (2013). An IT-enabled supply chain model: a simulation study. International Journal of Systems Science, 45(March 2015), 1– 15.

Cao, M., Vonderembse, M. A., Zhang, Q. Y., & Ragu-Nathan, T. S. (2010). Supply chain collaboration: conceptualisation and instrument development. International Journal of

Production Research, 48(22), 6613–6635.

Carr, A. S., & Pearson, J. N. (1999). Strategically managed buyer-supplier relationships and performance outcomes. Journal of Operations Management, 17(5), 497–519.

Carr, A. S., Kaynak, H., & Muthusamy, S. (2008). The cross-functional coordination between operations, marketing, purchasing and engineering and the impact on performance.

International Journal of Manufacturing Technology and Management, 13(1), 55.

Celo, S., Nebus, J., & Kim Wang, I. (2015). MNC structure, complexity, and performance: Insights from NK methodology. Journal of International Management, 21(3), 182–199. Cheng, Y., Farooq, S., & Johansen, J. (2015). International manufacturing network: past,

present, and future. International Journal of Operations & Production Management,

35(3), 392–429.

34 Christopher, M. (1992). Logistics & supply chain management. Logistics and Supply Chain

Management: Creating Value-adding Networks.

Clemmons, S., & Simon, S. J. (2001). Control and coordination in global ERP configuration.

Business Process Management Journal, 7(3), 205–215.

Cohen, W. M., & Levinthal, D. A. (1990). Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly, 35(1), 128.

Colotla, I., Shi, Y., & Gregory, M. J. (2003). Operation and performance of international manufacturing networks. International Journal of Operations & Production

Management, 23(10), 1184–1206.

Crespo, C. F., Griffith, D. A., & Lages, L. F. (2014). The performance effects of vertical and horizontal subsidiary knowledge outflows in multinational corporations. International

Business Review, 23(5), 993–1007.

Danese, P., Romano, P., & Vinelli, A. (2004). Managing business processes across supply networks: The role of coordination mechanisms. Journal of Purchasing and Supply

Management, 10(4–5 SPEC. ISS.), 165–177.

Devaraj, S., Krajewski, L., & Wei, J. C. (2007). Impact of eBusiness technologies on operational performance: The role of production information integration in the supply chain. Journal of Operations Management, 25(6), 1199–1216.

Dreyer, H. C., Alfnes, E., Strandhagen, J. O., & Thomassen, M. K. (2009). Global supply chain control systems: a conceptual framework for the global control centre. Production

Planning & Control, 20(2), 147-157

Droge, C., Jayaram, J., & Vickery, S. K. (2004). The effects of internal versus external integration practices on time-based performance and overall firm performance. Journal

of Operations Management, 22(6), 557–573.

Dubois, F. L., Toyne, B., & Oliff, M. D. (1993). International Manufacturing Strategies of U.S. Multinationals: A Conceptual Framework Based on a Four-Industry Study. Journal

of International Business Studies, 24(2), 307–333.

Eisenhardt, K. M. (1989). Building Theories from Case Study Research. Academy of

Management Review.

Eisenhardt, K. M., & Graebner, M. E. (2007). Theory building from cases: Opportunities and challenges. Academy of Management Journal, 50(1), 25–32.

Erhun, F., & Keskinocak, P. (2011). Collaborative Supply Chain Management. In Planning

Production and Inventories in the Extended Enterprise: A State of the Art Handbook,

Volume 1 (Vol. 151, pp. 233–268).

Fawcett, S. E., Birou, L., & Cofield Taylor, B. (1993). Supporting Global Operations through Logistics and Purchasing. International Journal of Physical Distribution & Logistics

35 Ferdows, K. (1989). Managing International Manufacturing. North Holland.

Ferdows, K. (2018). Keeping up with growing complexity of managing global operations.

International Journal of Operations & Production Management, 38(2), 390-402

Fey, C. F., & Furu, P. (2008). Top management incentive compensation and knowledge sharing in multinational corporations. Strategic Management Journal, 29(12), 1301– 1323.

Finnegan, P., & Longaigh, S. N. (2002). Examining the effects of information technology on control and coordination relationships: An exploratory study in subsidiaries of pan-national corporations. In Journal of Information Technology (Vol. 17, pp. 149–163). Flaherty, M. (1996). Global Operations Management. New York: McGraw-Hill.

Fortune, A., & Mitchell, W. (2012). Unpacking firm exit at the firm and industry levels: The adaptation and selection of firm capabilities. Strategic Management Journal, 33(7), 794– 819.

Frohlich, M. T. (2002). e-Integration in the Supply Chain: Barriers and Performance.

Decision Sciences, 33(4), 537–556.

Galbraith, J. R. (1974). Organization Design: An Information Processing View. Interfaces. https://doi.org/10.1287/inte.4.3.28

Germain, R., & Iyer, K. N. S. (2006). The Interaction of Internal and Downstream Integration and Its Association with Performance. Journal of Business Logistics, 27(2), 29–52. Gimenez, C., & Ventura, E. (2005). Logistics-production, logistics-marketing and external

integration. International Journal of Operations & Production Management, 25(1), 20– 38.

Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory. International

Journal of Qualitative Methods, 5, 1–10.

Gordon, R.L. (1975). Interviewing: Strategy, Techniques and Tactics. Dorsey Press.

Grandori, A., & Soda, G. (1995). Inter-firm Networks: Antecedents, Mechanisms and Forms.

Organization Studies, 16(2), 183–214.

Gupta, A. K., & Govindarajan, V. (1991). Knowledge Flows and the Structure of Control within Multinational Corporations. The Academy of Management Review, 16(4), 768. Gupta, D., & Weerawat, W. (2006). Supplier-manufacturer coordination in capacitated

two-stage supply chains. European Journal of Operational Research, 175(1), 67–89. Hayes, Pisano, Uprton, & Wheelwright. (2005). Operations, strategy, and technology: Pursuing the competitive edge. International Journal of Operations & Production

36 Holt, A. (2010). Using the telephone for narrative interviewing: A research note. Qualitative

Research.

Hu, J., 2004. Supplier Selection Determination and Centralized Purchasing Decisions. Ph.D. Dissertation. Washington State University, Pullman, WA.

Jonsson, P., Rudberg, M., & Holmberg, S. (2013). Supply Chain Management: An International Journal Centralised supply chain planning at IKEA Centralised supply chain planning at IKEA. An International Journal International Journal of Quality and

Service Sciences Iss Retail and Distribution Management, 18(3), 337–350.

Jüttner, U., & Maklan, S. (2011). Supply chain resilience in the global financial crisis: an empirical study. Supply Chain Management: An International Journal, 16(4), 246-259. Ketokivi, M., & Choi, T. (2014). Renaissance of case research as a scientific method. Journal

of Operations Management, 32(5), 232–240.

Ketokivi, M., & Schroeder, R. G. (2004). Perceptual measures of performance: Fact or fiction? Journal of Operations Management. 22(3), 247-264.

Kotler, P., Rackham, N., & Krishnaswamy, S. (2006). Ending the war between sales & marketing. Harvard Business Review. 84(7-8), 68-78.

Kulp, S. C., Lee, H. L., & Ofek, E. (2004). Manufacturer Benefits from Information Integration with Retail Customers. Management Science, 50(4), 431–444. Lee, Y. H., & Kim, S. H. (2002). Production-distribution planning in supply chain

considering capacity constraints. Computers and Industrial Engineering. 43(1), 169-190. Lehoux, N., D’Amours, S., & Langevin, A. (2014). Inter-firm collaborations and supply chain

coordination: review of key elements and case study. Production Planning & Control,

25(10), 858–872.

Leuschner, R., Rogers, D. S., & Charvet, F. F. (2013). A Meta-Analysis of Supply Chain Integration and Firm Performance. Journal of Supply Chain Management. 49(2), 34-57. Lorentz, H., Töyli, J., Solakivi, T., Hälinen, H. M., & Ojala, L. (2012). Effects of geographic

dispersion on intra-firm supply chain performance. Supply Chain Management: An

International Journal, 17(6), 611-626.

Malone, T. W., & Crowston, K. (1994). The interdisciplinary study of coordination. ACM

Computing Surveys, 26(1), 87–119.

Manuj, I., & Mentzer, J. T. (2008). Global supply chain risk management strategies.

International Journal of Physical Distribution & Logistics Management. 38(3), 192-223.

Mason, K. J., & Leek, S. (2008). Learning to build a supply network: An exploration of dynamic business models. Journal of Management Studies, 45(4), 774–799.

37 Meepetchdee, Y., & Shah, N. (2007). Logistical network design with robustness and

complexity considerations. International Journal of Physical Distribution & Logistics

Management, 37(3), 201–222.

Meijboom, B., & Vos, B. (1997). International manufacturing and location decisions: balancing configuration and co-ordination aspects. International Journal of Operations

& Production Management, 17(8), 790–805.

Miles, H. & Huberman, M. (1994). Qualitative data analysis: A Sourcebook (2nd ed.). Beverly Hills, CA: SAGE Publications.

Mintzberg, H. (1979). The Structuring of Organizations. Englewood Cliffs.

Monczka, R., Handfield, R., Giunipero, L. & Patterson, J. (2009). Purchasing and Supply

Chain Management. 4th ed. Mason, OH: South-Western Cengage Learning.

Mudambi, R., & Navarra, P. (2015). Is knowledge power? Knowledge flows, subsidiary power and rent-seeking within MNCs. In The Eclectic Paradigm (pp. 157-191). Palgrave Macmillan, London.

Narayanan, V. G., & Raman, A. (2001). Aligning in Supply Chains. Harvard Business

Review, 82(11), 94-102.

Netland, T. H., & Aspelund, A. (2014). Multi-plant improvement programmes: A literature review and research agenda. International Journal of Operations and Production

Management, 34(3), 390-418.

O’Donnell, S. W. (2000). Managing foreign subsidiaries: Agents of headquarters, or an interdependent network? Strategic Management Journal, 21(5), 525–548.

Patton, M. (1990). Qualitative Evaluation and Research Methods. Qualitative Evaluation and

Research Methods, 169–186.

Paulraj, A., & Chen, I. J. (2007). Strategic buyer-supplier relationships, information technology and external logistics integration. Journal of Supply Chain Management,

43(2), 2–14.

Pibernik, R., & Sucky, E. (2006). Centralised and decentralised supply chain planning.

International Journal of Integrated Supply Management, 2(1-2), 6-27.

Pontrandolfo, P., & Okogbaa, O. G. (1999). Global manufacturing: A review and a framework for planning in a global corporation. International Journal of Production

Research, 37(1), 1–19.

Prajogo, D., & Olhager, J. (2012). Supply chain integration and performance: The effects of long-term relationships, information technology and sharing, and logistics integration.

International Journal of Production Economics, 135(1), 514–522.

Prasad, S., & Babbar, S. (2000). International operations management research. Journal of