LOGISTICS OUTSOURCING IN FOOD PROCESSING INDUSTRY: A COMPLEXITY PERSPECTIVE

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LOGISTICS OUTSOURCING IN FOOD PROCESSING

INDUSTRY: A COMPLEXITY PERSPECTIVE

Master thesis, MSc, Supply Chain Management University of Groningen, Faculty of Economics and Business

Ruizhi Huang Student number [S2627205] E-mail: ruizhihuang168@gmail.com

r.huang@student.rug.nl

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ABSTRACT

Logistics outsourcing, a popular strategy for companies, is considered to help improve logistics performance. And its success and effectiveness have been proved in many industries. However, as the concept of supply chain complexity is proposed, the potential impact from logistics outsourcing on supply chain complexity has become an interesting topic. By means of survey in food processing industry, this paper tries to explore the relationship between logistics outsourcing, supply chain complexity and the characteristics of food processing industry. This provides the basis for future study on how to manage the supply chain complexity from logistics outsourcing.

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1. INTRODUCTION

Logistics outsourcing has become a popular strategy for companies to deal with problems related to logistics management which they may not be familiar with (Andersson and Norrman, 2002), or enhance value such as service promotion (Hsiao et al., 2010a). Hewlett Packard has outsourced its distribution to Fraure Machette to reduce its transportation and delivery uncertainty (Prater et al., 2001). World Food Programme has outsourced its logistics operations to a capable partner to improve response speed under disaster circumstance (Van Wassenhove, 2006).

The benefits of logistics outsourcing have been explained by multiple studies, including saving resources for core business (Nordin, 2008; Lau and Zhang, 2006), and cost reduction (McCarthy and Anagnostou, 2004; Bolumole et al., 2007) etc. The business practice nowadays has also approved the advantages of logistics outsourcing in different industries (Hsiao et al., 2010a). Because of the benefits mentioned above, logistics outsourcing becomes one of the most common business strategies (Chen et al., 2010). As logistics outsourcing has undeniably been largely adopted, some scholars also begin to pay attention to the potential dark sides of logistics outsourcing (e.g. Tsai et al., 2012). These dark sides include increasing supply chain geographical dispersion and supply chain complexity (Lu et al., 2014; De Leeuw et al., 2013; Hendricks et al., 2009). Since the growing degree of supply chain complexity results in business failure in many industries, the relationship between supply chain complexity and logistics outsourcing has become an interesting topic behind the great success of the adoption of logistics outsourcing (Kotabe and Mudambi, 2009). For example, to have the ability of fast response to the complex environment, companies who adopt logistics outsourcing even suffer new supply chain complexity (Yang and Yang, 2010). Hendricks et al. (2009) have also indicated that a high degree of logistics outsourcing may make it harder to control over certain logistics processes, resulting in the growth of supply chain complexity.

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potential risk of logistics outsourcing adoption from a SCM (supply chain management) point of view, which does not fully illustrate that how supply chain complexity occurs under logistics outsourcing. This indicates that in fact, we still do not know whether logistics outsourcing will lead to the growth of supply chain complexity, and if so, what kinds of supply chain complexity will occur. Therefore, to fill the gap in theory, more research should be done to explore the direct effect of logistics outsourcing on supply chain complexity. And the results of the research should be able to contribute to managerial aspect, i.e. giving an inspiration on what kinds of supply chain complexity may exist when adopting certain logistics outsourcing strategies.

This paper will focus on the logistics outsourcing in food processing industry. As mentioned by Hsiao et al. (2010a), although there are some of the studies realizing the importance of logistics management in food processing industry (e.g. Omta, 2004; Van der Vorst et al., 2005; Van der Vorst and Beulens, 2002), little research has been done on implication of logistics outsourcing for food supply chains. Besides that, the characteristics of food processing industry make logistics planning far more complicated than other industries (Hsiao et al., 2010b). Characteristics of food processing industry mentioned by multiple papers (e.g. Van Donk, 2001; Georgiadis et al., 2005) include the variability in customer demands and perishability, making logistics outsourcing in food processing industry more complex (Shukla and Jharkharia, 2013) and well worth studying. These all suggest that it is more meaningful to study the management of logistics outsourcing in food processing industry.

Therefore the purpose of this paper is to explore whether there is effect of logistics outsourcing on supply chain complexity in the food processing industry. Based on this, evidence will be provided for the future study on supply chain complexity management. The main research question will be: Does logistics outsourcing in food processing industry lead to the increase of supply chain complexity? If so, what kinds of supply chain complexity will occur?

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first stage, the possible logistics outsourcing activities in food processing industry and the supply chain complexity related to logistics outsourcing will be classified based on literature review. In stage two, based on the items identified from stage one, a survey will be conducted to examine the logistics outsourcing adopted by organizations and their impact on supply chain complexity. In the final stage the results from survey will be analysed and discussed.

2. THEORETICAL BACKGROUND

2.1 Logistics outsourcing

Outsourcing is the shortened form of “outside resource using” (Hsiao et al., 2006, P.2), and it is largely adopted by companies who are facing to the competitive environment (Lu et al., 2014). Outsourcing can be divided into core business outsourcing and non-core business outsourcing, while logistics outsourcing belongs to non-core business outsourcing, meaning that the organisation uses an external service provider to cover the activities related to logistics management instead of performing it in-house (Wang et al., 2006).

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Figure 2.1: Framework of levels of logistics outsourcing

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Classification Services Segmentations

1st level

Transportation

Warehousing

Delivery; order picking

Storage; receiving

2nd level

Transportation management

Inventory management

Route planning and scheduling; mode selection; rate negotiation; tracking and event control

Forecasting; stock control 3rd level Total outsourcing Logistics network design; logistics

solutions

Table 2.1: Classification of logistics outsourcing (adaption from Hsiao et al., 2009)

2.2 Supply chain complexity

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As agreed by most of the studies, supply chain complexity can be classified as structural (static) complexity and operational (dynamic) complexity (e.g. Frizelle and Woodcock, 1995; Sivadasan et al., 2002). Structural complexity is related to complicatedness of the physical structure, while operational complexity is related to the uncertainty in operational system (Calinescu et al., 1998; Sivadasan et al., 2002). In the scenario of logistics outsourcing, the structural complexity refers to e.g. demand variability and number of suppliers etc., while the operational complexity refers to e.g. delivery reliability (Bozarth et al., 2009; Hsiao et al., 2010b). Thus, considering the relationship between logistics outsourcing decision making and structural/operational complexity, we believe that structural complexity will influence

logistics outsourcing decision making, and the actual logistics outsourcing decision making will influence operational complexity (Figure 2.2). In this paper, we try to explore the potential supply chain complexity resulting from logistics outsourcing decision making, therefore this paper will focus on operational complexity.

Figure 2.2: Relationship between logistics outsourcing decision making and structural/operational complexity

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complexity in management systems consists of the frequency of production scheduling changes, delay of product delivery and the volatility of the demand, which creates additional unpredictability for organizations.

Uncertainty Segmentations

Process/product structure

Process capability of the focal firm Process capability of suppliers

Throughput time variation and stochastic set-up time

Management systems

Production scheduling changes Late product delivery

Demand volatility

Table 2.2: Operational supply chain complexity (from Vachon and Klassen, 2002)

2.3 Characteristics of food processing industry

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Categories Segmentations Plant characteristics Single-purpose production lines

Long set-up times

Product characteristics Variety in supply, quality and price of raw material

Perishability in raw material, semi-manufactured and end products

Production process characteristics

Variety in production time Divergent product structure

Multiple and variable production processes

Table 2.3: Characteristics of FPI (adaption from Van Donk, 2001)

2.4 Research framework

Previous sections discuss separately about the levels of logistics outsourcing, different supply chain complexity and the characteristics of food processing industry. In this section, the potential relationships of these three variables will be discussed. These potential relationships include the impact of logistics outsourcing on supply chain complexity, as well as the enhancement effect of characteristics of food processing industry on the logistics outsourcing and supply chain complexity relationship.

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logistics outsourcing will increase supply chain complexity in a certain extent, and that the extent of complexity is related to the degrees of logistics outsourcing i.e. different levels of logistics outsourcing will have distinct impact on supply chain complexity. Overall, logistics outsourcing may have a positive effect on supply chain complexity, this paper formulates the following hypothesis:

H1. Logistics outsourcing may increase supply chain complexity (different levels of logistics

outsourcing may have different results).

Despite the direct effect from logistics outsourcing on supply chain complexity, the characteristics of a certain industry may also influence the degree of complexity. To investigate it, this paper chooses food processing industry as the research target. Few studies have investigated the characteristics of a certain industry as a moderator to logistics outsourcing and complexity relationship. However, as for food processing industry, many scholars have agreed that the characteristics of FPI add complexity to the context (Grievink et al., 2002; Ahumada and Villalobos, 2009; Shukla and Jharkharia, 2013). For example, in food processing industry (FPI), the seasonality in raw material supply and perishability of the end products make it more complex for logistics planning (Grievink et al., 2002). According to Mentzer et al. (2001), food processing industry involves raw/intermediate/end food production activities and related services. Due to the development in the past decades, food processing industry has become more complex and also brings more complexity to its related service aspects (Hsiao et al., 2006). As Ahumada and Villalobos (2009) have pointed out, the shorter shelf life of raw materials/end products in food processing industry requires shorter lead time, which makes it more difficult for i.e. transportation. The fact that the demands are fluctuated and varied also increases the degree of complexity of distribution in food processing industry than the others (Shukla and Jharkharia, 2013).

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logistics planning more difficult and complex. Therefore, to achieve the research objective, this paper will not only examine the general effect of logistics outsourcing on supply chain complexity, but also try to investigate how the characteristics of FPI moderates the relationship between logistics outsourcing and supply chain complexity. Thus, this paper formulates the following hypothesis:

H2. The characteristics of food processing industry will enhance the effect of logistics

outsourcing on supply chain complexity.

Based on the discussion above, the research framework for this paper is formed (Figure 2.2).

Figure 2.3: Research framework

3. METHODOLOGY

3.1 Research Method

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3.2 Measures and Questionnaire

In the survey, questionnaire is designed based on three constructs, i.e. the levels of logistics outsourcing, the degree of supply chain complexity and the characteristics of food processing industry. All questions are asked in 5 likert scales.

There are three different levels of logistics outsourcing in both transportation and warehousing (Hsiao et al., 2006; Hsiao et al., 2010a; Hsiao et al., 2010b). Questions in this part are designed to ask the respondents about the level of transportation and warehousing outsourcing, and the degree of their logistics activities outsourcing in each level (Table 3.1).

Activities The 1st level The 2nd level The 3rd level

Transportation

Delivery; order-picking

Route planning and scheduling; mode selection; rate negotiation; tracking and event control

Logistics (transportation) network design Not outsourced To Fully outsourced Not outsourced To Fully outsourced Not outsourced To Fully outsourced Warehousing Storage; receiving

Sales forecasting; stock control Logistics (warehousing) network design Not outsourced To Fully outsourced Not outsourced To Fully outsourced Not outsourced To Fully outsourced

Table 3.1: Measures for levels of logistics outsourcing (Hsiao et al., 2006; Hsiao et al., 2010a; Hsiao et al., 2010b)

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material (%), work-in-process failures (%) and rejects at the final inspection (%). In management systems part, two items will be asked: scheduling change (%) and make-to-order production (%). High percentages mean that the company has higher degree of supply chain complexity. Structure and System Complexity are called for short for the two constructs respectively.

Complexity Items (%)

Structure

Rejects of incoming material Work-in-process failures Rejects at the final inspection System Production scheduling change

Make-to-order production

Table 3.2: Measures for degree of operational complexity (Vachon and Klassen, 2002)

In part of characteristics of food processing industry, respondents will answer with their perception about the situation of their own companies. This part will include eight items associated with three constructs, namely Plant, Product and Production Characteristics.

Characteristics Perception

Plant The product types produced by a single line Set-up time

Product

Shelf life of raw materials Shelf life of semi products Shelf life of end products

Production

Variability in production time Difference in product structure Variability in production processes

Table 3.3: Measures for Characteristics of FPI (Van Donk, 2001)

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3.3 Sample and Data Collection

Data for the survey was collected by sending questionnaires to food processing companies in China, considering the tremendous growing trend of third party logistics service usage in Chinese manufacture industry. And with the huge number of food processing companies, it should be possible to gather enough amounts of data for analysis. Questionnaires were sent online to the members of China National Food Industry Association (CNFIA). Among the 374 questionnaires sent by email, finally there are 46 responses, 3 of them are unusable because unfinished. The data collection period was from 3rd December 2015 to 3rd January 2016, with a response rate of 13%. General questions are asked to acquire the food sectors they belong to, firm size (number of employees and product groups).

We divide the food industries into 6 sectors, named meat, fish, dairy, beverage, fruit and vegetable, and others. Among 43 companies which provide usable responses, 5 of them belong to meat sector, 3 are from fish, 7 are from dairy sector, 8 belong to beverage, 6 are from fruit and vegetables, remaining are from others (including snack, fast food, health care product etc.).

Sectors Meat Fish Dairy Beverage Fruit and vegetables Others

Frequency 5 3 7 8 6 14

Percentage 11.6 7.0 16.3 18.6 14.0 32.6

Table 3.4 Sectors of Food Processing Companies

While considering the firm size, the majority of the companies are rather small (with small amount of employees and product groups).

Number of employees 1-40 41-50 51-100 101-200 More than 200

Frequency 12 12 8 6 5

Percentage 27.9 27.9 18.6 14.0 11.6

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Number of product groups 1 2 3 4 More than 4

Frequency 3 23 10 3 4

Percentage 7.0 53.5 23.3 7.0 9.3

Table 3.6 Number of Product Groups

Based on the sample size, KMO and Barlett’s Test was firstly conducted to check whether the sample size is adequate for factor analysis and whether there are relationships between items that we are hoping for.

KMO Measure of Sampling Adequacy .670

Bartlett's Test of Sphericity (Sig.) .000

Table 3.7 Result of KMO and Barlett’s Test

As shown in Table 3.7, KMO is .670, larger than .600, which means that the sample size we got is adequate. In addition, the result of Barlett’s Test is significant (<.05), meaning that there are relationships underlying.

3.4 Construct Validation

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Factor analysis of Structure Complexity

Structure Complexity is a construct to describe the complexity in process/product structure, including 3 items i.e. material reject, WIP failure and final inspection reject rate. The result of Cronbach’s Alpha Test is .441, and final inspection reject rate shows little correlation with the other two items. Thus it is deleted from construct Structure Complexity, and the latter result from Cronbach’s Alpha Test is .560, though not high enough, as the sample size is rather small, it is acceptable.

Factor analysis of System Complexity

System Complexity is a construct to describe the complexity in management systems, including 2 items i.e. schedule change and make-to-order frequency. The result of Cronbach’s Alpha Test is .633, which means this construct is acceptable.

Factor analysis of Plant Characteristics

Plant Characteristics is a construct to describe the plant characteristics of the companies, including 2 items i.e. production type and set-up time. The result of Cronbach’s Alpha Test is .380, too low for describing the same construct. As this construct has only 2 items and no room for improvement, the whole construct is deleted.

Factor analysis of Product Characteristics

Product Characteristics is a construct to describe the product characteristics of the companies, including 3 items i.e. raw material, semi product and end product shelf life. The result of Cronbach’s Alpha Test is .798, high enough for continuing using.

Factor analysis of Production Characteristics

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Characteristics 3, and the latter result from Cronbach’s Alpha Test is .530, though not high enough, as the sample size is rather small, it is acceptable for new scales.

In conclusion of factor analysis, two items are deleted from two separate constructs, and one construct is deleted because of low result from Cronbach’s Alpha Test, making it 3 constructs of independent variables, 2 constructs of dependent variables, 2 constructs of moderators (Table 3.8).

Variables Constructs Items Results

Independent variables

The 1st level of logistics outsourcing The 2nd level of logistics

outsourcing The 3rd level of logistics

outsourcing

Dependent variables

Structure Complexity

Material reject rate WIP failure rate

Final inspection reject rate Deleted System Complexity Schedule change frequency

Make-to-order production frequency

Moderators

Plant Characteristics Production type Deleted Set-up time

Product Characteristics

Raw material shelf life Semi product shelf life End product shelf life

Production Characteristics

Variant in production time Divergent product structure

Variability in production process Deleted

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Based on the result of construct validation, mean standard deviations and correlations are presented in Table 3.9.

Mean S. D. 1 2 3 4 5 6

1. The 1st level of logistics outsourcing

3.77 1.284

2. The 2nd level of logistics outsourcing

1.79 1.450 -.243

3. The 3rd_{level of logistics}

outsourcing 1.07 1.758 -.311* _-.115 4. Structure Complexity 2.53 .627 .589** _-.046 _-.380* 5. System Complexity 2.28 .868 .472** _-.014 _.017 _.569** 6. Product Characteristics 2.60 .615 .367* -.068 -.420** _.773** _.399** 7. Production Characteristics 2.57 .684 -.017 -.041 .131 .047 -.038 .052 *. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

Table 3.9: Descriptive statistics and correlations.

4. RESULTS

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Figure 4.1: New framework for data analysis

4.1 The 1

st

_{level and Product Characteristics on Structure Complexity}

This part studies whether there is direct effect from the 1st level of logistics outsourcing and whether there is moderating effect from Product Characteristics on Structure Complexity. As shown in Table 4.1, there is direct effect from the 1st level of logistics outsourcing and Product Characteristics (p<.05), but no moderating effect from Product Characteristics (p>.05). The 1st level of logistics outsourcing and Product Characteristics are positively related to Structure Complexity (B=.20 and B=.42).

Variables B p-value

The 1st level (logistics outsourcing) .204 .001 Moderator: Product Characteristics .422 .000 Interaction: The 1st level×Product Characteristics .090 .154

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4.2 The 1

st

_{level and Product Characteristics on System Complexity}

This part studies whether there is direct effect from the 1st level of logistics outsourcing and whether there is moderating effect from Product Characteristics on System Complexity. As shown in Table 4.2, there is direct effect from the 1st level of logistics outsourcing and Product Characteristics (p<.05), but no moderating effect from Product Characteristics (p>.05). The 1st level of logistics outsourcing and Product Characteristics are positively related to System Complexity (B=.30 and B=.26).

Variables B p-value

The 1st level (logistics outsourcing) .296 .025 Moderator: Product Characteristics .260 .048 Interaction: The 1st level×Product Characteristics .166 .225

Table 4.2: Effect on System Complexity

4.3 The 1

st

_{level and Production Characteristics on Structure Complexity}

This part studies whether there is direct effect from the 1st level of logistics outsourcing and whether there is moderating effect from Production Characteristics on Structure Complexity. As shown in Table 4.3, there is direct effect from the 1st level of logistics outsourcing (p<.05), but no moderating effect from Production Characteristics (p>.05). The 1st level of logistics outsourcing is positively related to Structure Complexity (B=.39).

Variables B p-value

The 1st level (logistics outsourcing) .391 .000 Moderator: Production Characteristics .031 .693 Interaction: The 1st level×Production Characteristics .140 .064

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4.4 The 1

st

_{level and Production Characteristics on System Complexity}

This part studies whether there is direct effect from the 1st level of logistics outsourcing and whether there is moderating effect from Production Characteristics on System Complexity. As shown in Table 4.4, there is direct effect from the 1st level of logistics outsourcing (p<.05), and moderating effect from Production Characteristics (p<.05). The 1st level of logistics outsourcing is positively related to Structure Complexity (B=.39), and the Production Characteristics enhances the direct effect (B=.29).

Variables B p-value

The 1st level (logistics outsourcing) .454 .000 Moderator: Production Characteristics .036 .749 Interaction: The 1st level×Production Characteristics .288 .010

The slope chart is as followed:

Figure 4.2: Slope chart of moderating effect

As the chart shows, the moderating effect of production characteristics enhances the direct

1

1.5

2

2.5

3

3.5

4

4.5

5 Low The 1st level

High The 1st level

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effect from the 1st level logistics outsourcing on System Complexity.

4.5 The 2

nd

_{level and Product Characteristics on Structure Complexity}

This part studies whether there is direct effect from the 2nd level of logistics outsourcing and whether there is moderating effect from Product Characteristics on Structure Complexity. As shown in Table 4.5, there is neither direct effect from the 2nd level of logistics outsourcing, nor moderating effect from Product Characteristics (p>.05).

Variables B p-value

The 2nd level (logistics outsourcing) .008 .902 Moderator: Product Characteristics .503 .000 Interaction: The 2nd level×Product Characteristics .133 .063

Table 4.5: Effect on Structure Complexity

4.6 The 2

nd

_{level and Product Characteristics on System Complexity}

This part studies whether there is direct effect from the 2nd level of logistics outsourcing and whether there is moderating effect from Product Characteristics on System Complexity. As shown in Table 4.6, there is neither direct effect from the 2nd level of logistics outsourcing, nor moderating effect from Product Characteristics (p>.05).

Variables B p-value

The 2nd level (logistics outsourcing) .018 .887 Moderator: Product Characteristics .379 .004 Interaction: The 2nd level×Product Characteristics .229 .113

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4.7 The 2

nd

_{level and Production Characteristics on Structure Complexity}

This part studies whether there is direct effect from the 2nd level of logistics outsourcing and whether there is moderating effect from Production Characteristics on Structure Complexity. As shown in Table 4.7, there is neither direct effect from the 2nd level of logistics outsourcing, nor moderating effect from Production Characteristics (p>.05).

Variables B p-value

The 2nd level (logistics outsourcing) -.045 .664 Moderator: Production Characteristics .019 .855 Interaction: The 2nd level×Production Characteristics .053 .527

4.8 The 2

nd

_{level and Production Characteristics on System Complexity}

This part studies whether there is direct effect from the 2nd level of logistics outsourcing and whether there is moderating effect from Production Characteristics on System Complexity. As shown in Table 4.8, there is neither direct effect from the 2nd level of logistics outsourcing, nor moderating effect from Production Characteristics (p>.05).

Variables B p-value

The 2nd level (logistics outsourcing) -.043 .767 Moderator: Production Characteristics -.050 .723 Interaction: The 2nd level×Production Characteristics .088 .445

4.9 The 3

rd

_{level and Product Characteristics on Structure Complexity}

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whether there is moderating effect from Product Characteristics on Structure Complexity. As shown in Table 4.9, there is neither direct effect from the 3rd level of logistics outsourcing, nor moderating effect from Product Characteristics (p>.05).

Variables B p-value

The 3rd level (logistics outsourcing) -.114 .447 Moderator: Product Characteristics .461 .000 Interaction: The 3rd level×Product Characteristics -.049 .589

4.10 The 3

rd

_{level and Product Characteristics on System Complexity}

This part studies whether there is direct effect from the 3rd level of logistics outsourcing and whether there is moderating effect from Product Characteristics on System Complexity. As shown in Table 4.10, there is neither direct effect from the 3rd level of logistics outsourcing, nor moderating effect from Product Characteristics (p>.05).

Variables B p-value

The 3rd level (logistics outsourcing) -.101 .726 Moderator: Product Characteristics .405 .005 Interaction: The 3rd level×Product Characteristics -.204 .249

4.11 The 3

rd

_{level and Production Characteristics on Structure}

Complexity

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(p<.05), but no moderating effect from Production Characteristics (p>.05). The 3rd level of logistics outsourcing is negatively related to Structure Complexity (B=-.24)

Variables B p-value

The 3rd level (logistics outsourcing) -.239 .026 Moderator: Production Characteristics .061 .517 Interaction: The 3rd level×Production Characteristics -.017 .867

4.12 The 3

rd

_{level and Production Characteristics on System Complexity}

This part studies whether there is direct effect from the 3rd level of logistics outsourcing and whether there is moderating effect from Production Characteristics on System Complexity. As shown in Table 4.12, there is neither direct effect from the 3rd level of logistics outsourcing, nor moderating effect from Production Characteristics (p>.05).

Variables B p-value

The 3rd level (logistics outsourcing) .031 .843 Moderator: Production Characteristics -.037 .795 Interaction: The 3rd level×Production Characteristics -.025 .867

5. DISCUSSION

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logistics activities, companies are more likely to face supply chain complexity. Additionally, Production Characteristics has shown a moderating and positive effect on the relationship between the 1st level of logistics outsourcing and supply chain complexity. Based on these findings, the discussion of this paper will focus on three parts: a) The impact of logistics outsourcing on supply chain complexity; b) The impact of characteristics of FPI on outsourcing-complexity relationship; c) Other unexpected results.

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The potential moderating effect from Product and Production Characteristics are explored in data analysis. Production Characteristics shows an moderating effect that enhances the positive effect of the 1st level logistics outsourcing on supply chain complexity, which means that with a more variant or divergent production process, companies who adopt 1st level logistics are more likely to face supply chain complexity. This is also in accordance with most of the existing theory, as most of the scholars have pointed out the variability is the one should be managed to keep production process stable and consistent (Zeng and Zhou, 2008; He et al., 2007; Paladini et al., 2015). Additionally, most of the scholars agree that adding buffers is one of the effective strategies to mitigate variability in production process, including Material Requirement Planning and postponement (Levalle et al., 2013; Van Donk, 2011). As food processing is time sensitive, it is hard to add buffer in inventory (keeping high level of safety stocks), because the raw materials, semi and final products are easy to perish. Therefore, it is reasonable to adopt logistics postponement, requiring higher level of integration or collaboration with 3PL providers, which is still not common in Chinese food processing industry.

Beyond our expectations, Product Characteristics (the perishability of raw materials, semi and final products) does not show a positive moderating effect. Instead, it shows a direct and positive effect on supply chain complexity, which indicates that perishability is a critical issue in food processing industry. Companies who have not dealt well with this characteristic may face a dilemma: either a high level of safety stocks or material shortage. Vendor Managed Inventory may be a good method in controlling material stock level in food processing industry, as it could reduce not only the procurement cost but also the inventory level and keep materials in good quality.

6. CONCLUSION

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which is rather a blank in theory. Considering the research circumstances, this paper chooses food processing industry as target industry, because some of the characteristics in food processing industry are rather different and critical compared with other industries. This paper uses the data from 43 Chinese food processing companies to conduct a survey. Based on the result of data analysis, we have found that in the survey, 1st logistics outsourcing have positive effect on supply chain complexity, and the characteristics of production process of FPI act as a moderator, enhancing the relationship. Additionally, the characteristic of perishability is found to be critical in food processing industry. Therefore, we can provide answers to the research question that the 1st level of logistics outsourcing (traditional logistics outsourcing) may result in the increase of supply chain complexity, and the variability in production characteristics of FPI enhances that relationship.

Considering these findings, we can say that we successfully contribute to theory, as normally, scholars will treat logistics outsourcing as a solution to reduce supply chain complexity. Few studies have considered the disadvantages of logistics outsourcing regarding supply chain complexity. Based on the findings, we give out several reasonable strategies to manage the potential supply chain complexity from logistics outsourcing and characteristics of FPI. These recommendations may not be general, but they are focusing on the situation of Chinese food processing industry. In conclusion, this paper provides a new angle when considering logistics outsourcing, which contributes to not only theory but also managerial issues.

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APPENDIX

Part 1: General questions

General questions about product groups, number of employees etc. are asked for the purpose of controlled variables.

1. What sector of food does your company belong to?

A. Meat B. Fish C. Dairy D. Beverage E. Fruit and vegetable F. Others

2. How many full time employees are there at your company?

A. 1-40 B. 41-50 C. 51-100 D. 101-200 E. More than 200

3. How many product groups does your company have in the region?

A. 1 B. 2 C. 3 D. 4 E. More than 4

Part 2: Level of logistics outsourcing

We would like to know the level of logistics outsourcing of the largest product group in your company.

The level of logistics outsourcing

Transportation

1st level (including delivery, order-picking)

□Not outsourced to □Fully outsourced (Scale 1 to 5)

2nd level (including route planning and scheduling, mode selection, rate negotiation, tracking and event control)

□Not outsourced to □Fully outsourced (Scale 1 to 5) 3rd level (Transportation network design)

□Not outsourced to □Fully outsourced (Scale 1 to 5) Warehousing

1st level (including storage, receiving)

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32 3rd level (Warehousing network design)

□Not outsourced to □Fully outsourced (Scale 1 to 5)

Part 3: degree of supply chain complexity

We would like to know the degree of complexity of the largest product group in your company.

The degree of complexity of the largest product group in your company

Process/product structure

1. What is the reject rate of incoming material of the product group?

A. Less than 1% B. 1-5% C. 6-10% D. 11-20% E. More than 20%

2. What is the percentage of work-in-process failures?

3. What is the reject rate at the final inspection?

Management systems

1. What is the percentage of production scheduling change?

2. What is the percentage of make-to-order production?

Part 4: characteristics of food processing industry

We would like to know to what extent you agree about the characteristics of your company, as a food processing company.

The characteristics of your company

Plant characteristics

1. How many different kinds of products can be produced by a single production line?

A. More than 4 B. 4 C. 3 D. 2 E. 1

2. How long is the set-up time between production?

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Product characteristics

1. How long can you keep raw materials/semi-manufactured and end products in good quality (days)? Raw materials: A. More than 10 B. 7-10 C. 4-6 D. 2-3 E. 0-1

Semi-manufactured products: A. More than 10 B. 7-10 C. 4-6 D. 2-3 E. 0-1 End products: A. More than 10 B. 7-10 C. 4-6 D. 2-3 E. 0-1

Production process characteristics (1-5 low-high difference)

1. To what extent do you perceive the variability in production time of different products?

A. 1 B. 2 C. 3 D. 4 E. 5

2. To what extent do you perceive the different product structure?

A. 1 B. 2 C. 3 D. 4 E. 5

3. To what extent do you perceive the variability in production processes?

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LOGISTICS OUTSOURCING IN FOOD PROCESSING INDUSTRY: A COMPLEXITY PERSPECTIVE