Degree Project
Supplier Information Integration
for Mitigating Supply Risk in
Chinese and Thai Manufacturing
Industries
Authors:
Chanat Preechawipat,
Summary
Business Administration, Business Process & Supply Chain Management, Degree Project (Master), 30 higher education credits, 5FE02E, Spring 2012
Authors: Chanat Preechawipat and Kai Zhang
Tutor: Åsa Gustavsson
Title: Supplier Information Integration for Mitigating Supply Risk in Chinese and Thai Manufacturing Industries
Background: Supply risk becomes a crucial risk that manufacturing companies are facing while supplier information integration is one of the most important parts of supply chain management and supplier integration. The research based on the relationship between them is rarely found.
Purpose: To find, describe, and compare the significant relationship of supplier information integration and supply risk and identify whether supplier information integration can help to mitigate supply risk in Chinese and Thai manufacturing industries.
Methods: In order to answer the research questions, the search of the relevant literatures were carried out. The theoretical frame was made of basic concepts, approaches of supplier information integration, and sources of supply risk. The questionnaire was designed based on the theoretical framework and sent out among Chinese and Thai listed manufacturing companies. The correlation analysis was carried out as the main approach to check the significant relationships while the descriptive statistics were used to described, compared, and analyzed in order to indentify the level of SII and perception of supply risk.
Conclusion: The level of supplier information integration and the perception of supply risk showed differences in Chinese and Thai manufacturers. Chinese manufacturing industry was at medium level of IT and share tactical and strategic information with suppliers with a concern on suppliers’ suppliers while the Thai manufacturing industry was at low level of IT and shared only tactical information with suppliers with very less concern on suppliers’ suppliers. Chinese manufacturers showed an obvious lower perception of getting affected by terrorist incidents and natural disasters while Thai manufacturers showed the same perception of all sources of supply risk. The results indicated that most of relationships between the sub items of supplier information integration and supply risk were not significant with some special cases that showed small and medium relationships. The contribution and suggestion were concluded at the end.
Keywords: Supplier information integration, information integration, information sharing, supply risk
Acknowledgements
This master thesis is an output of dedication and contribution involving many people during spring 2012. The thesis was written and elaborated at Linnaeus University, Växjö, Sweden guided by our honorable academic persons, Helena Forslund and Åsa Gustavsson.
First of all, we want to thank our examiner, Associate Professor Helena Forslund, for her leadership, competence, and patience during the time that this thesis has been worked on. We also would like to thank our tutor, Dr. Åsa Gustavsson, for her guidance, feedback, and encouragement that brought us the motivation and alignment throughout the working process. Furthermore, we want to show our gratitude to our classmates, especially our opposing group for giving critics and suggestions that helped us improved our competency.
We appreciate many respondents who saw our thesis valuable and cheered up during hard time of data collection process.
Many thanks to all friends, teachers, old colleagues, business partners, family, and relatives in China and Thailand for being a source of inspiration to us that finally led us accomplished the thesis.
Finally, we would like to send a special thank to Sweden for giving this educational opportunity and as being a warm host and open-minded that allowed us to explore and experience a new world and friendships that governed an optimistic view after finishing the thesis.
All we want to say,
“Thank You”, “Tack”, “谢谢”, and “ขอบคุณคะ”
Växjö, May 2012
Abbreviations
This section underlines all the abbreviations and specific terms used in this thesis providing the page number where the terms are started to be used.
BCP: Business Continuity Planning, see p.57
CPFR: Collaborate Planning, Forecasting and Replenishment, see p.43 CPI: China Customer Price Index, see p.51
CRM: Customer Relationship Management, see p.43 CRP: Continuous Replenishment Programs, see p.43 DIS: Demand Information Sharing, see p.46
EDI: Electronic Data Interchange, see p.42 ERP: Enterprise Resource Planning, see p.42 GDP: The Gross Domestic Products, see p.15 IT: Information Technology, see p.14
IS: Information Sharing, see p. 55
NICs: Newly Industrialized Countries, see p.15 NIS: No Information Sharing, see p.46
OIS: Order Information Sharing, see p.46 p: Significance Level, see p.35
POS: Point-of-Sale, see p.43 QR: Quick Response, see p.43
r: Correlation Coefficient value, see p.35 RFID: Radio Frequency Identification, see p.57 S.D.: Standard Deviations, see p.62
SC: Supply Chain, see p.44
SCI: Supply Chain Integration, see p.13 SCM: Supply Chain Management, see p.13 SCP: Supply Chain Planning, see p.44
SII: Supplier Information Integration, see p.15 VMI: Vendor Managed Inventory, see p.43 XML: Extensible Markup Language, see p.42
List of Figures
Figure 1: The focus of the thesis ... 18
Figure 2: Deposition of this thesis ... 20
Figure 3: The research “onion” ... 22
Figure 4: Research choices ... 30
Figure 5: Sampling techniques ... 32
Figure 6: A model of different risk sources and their links to three types of risk sources and their links to the three types of risk. ... 50
Figure 7: Summarized conceptual model of relationships among supplier information integration and supply risk ... 56
List of Tables
Table 1: Major differences between deductive and inductive approaches
to the research ... 25
Table 2: Research strategy for this thesis ... 28
Table 3: Distribution of the sampling frame and the respondents ... 34
Table 4: Distribution of work year from the respondents ... 34
Table 5: Summary of research methodology of this thesis ... 38
Table 6: Research questions and respective theories ... 39
Table 7: Stages of information integration ... 44
Table 8: Summary of theory of this thesis ... 55
Table 9: Reliabilities coefficients ... 62
Table 10: Descriptive statistics of information technology ... 63
Table 11: Descriptive statistics of information sharing from manufacturer to supplier ... 64
Table 12: Descriptive statistics of information sharing from supplier to manufacturer ... 65
Table 13: Descriptive statistics of supply risk ... 66
Table 14: Descriptive statistics of probability of supply risk ... 67
Table 15: Descriptive statistics of impact of supply risk ... 67
Table 16: Relationships between supplier information integration and supply risk in Chinese manufacturing industry ... 69
Table 17: Relationships between supplier information integration and supply risk in Thai manufacturing industry ... 73
Table 18: Results of correlation analysis ... 77
Table of Contents
Summary ... 2 Acknowledgements ... 4 Abbreviations ... 5 List of Figures ... 6 List of Tables ... 7 1. Introduction ... 11 1.1 Background ... 111.1.1 Changing Supply Chain Environment ... 11
1.1.2 The Focus on How to Manage Company Risk... 12
1.1.3 Supply Chain Integration ... 13
1.1.4 Supplier Information Integration ... 14
1.2 Problem Discussion ... 15
1.2.1 The View on China and Thailand ... 15
1.2.2 Supply Risk and SII in Manufacturing Industry ... 16
1.2.3 The Link to Research Questions ... 17
1.3 Research Question ... 19 1.4 Purpose ... 19 1.5 Thesis Deposition ... 20 1.6 Delimitation ... 21 2. Research Methodology ... 22 2.1 Research Philosophies ... 23 2.2 Research Approaches ... 24 2.3 Research Strategies ... 26 2.4 Research Choices ... 29 2.5 Time Horizons ... 31
2.6 Data Collection and Data Analysis ... 31
2.6.1 Population and Sampling ... 31
2.6.2 Translation and Transformation ... 34
2.6.3 Data analysis ... 35
2.7 Research Credibility ... 36
2.7.1 Validity ... 36
2.7.2 Reliability ... 37
3. Theory ... 39
3.1 Supplier Information Integration ... 40
3.1.1 Introduction of Supplier Information Integration ... 40
3.1.2 Information Technology ... 41
3.1.3 Information Sharing ... 44
3.2 Supply Risk ... 47
3.3 Macro Environments in China and Thailand ... 51
3.3.1 China ... 51
3.3.2 Thailand ... 52
3.4 Summary of Theory ... 54
4. Generation of Hypotheses ... 56
4.1 SII Antecedents to Mitigating Supply Risk ... 57
4.2 Nationalities: China and Thailand ... 59
5. Empirical Findings ... 61
5.1 Reliability Analysis ... 61
5.2 Descriptive Statistics ... 62
5.2.1 Descriptive Statistics for Supplier Information Integration ... 62
5.2.2 Descriptive Statistics for Supply Risk ... 66
5.3 Correlation Analysis ... 68
5.3.1 Correlation Analysis for Chinese Manufacturing Industry ... 69
5.3.2 Correlation Analysis for Thai Manufacturing Industry ... 72
5.3.2 Summary of Correlations ... 76 6. Analysis ... 78 6.1 Research Question 1 ... 78 6.2 Research Question 2 ... 81 6.3 Research Question 3 ... 83 7. Conclusion ... 89
7.1 Answers of research questions ... 89
7.2 Theoretical Contribution ... 90
7.2 Practical Contribution ... 91
7.3 Reflections ... 91
7.4 Recommendation ... 92
7.5 Critiques of this thesis ... 92
APPENDIX ... 106
I. Questionnaire ... 106
II. Operationalization of Concepts ... 112
III. Correlations in Chinese Industry ... 114
IV. Summary of Correlations from Chinese Manufacturing Industry ... 123
V. Correlations in Thai Industry ... 124
1. Introduction
he first chapter includes a background which is comprised of subjects motivated to the research problem that limits the scope of supplier information integration aiming for mitigating supply risks in manufacturing industry. Further, the research problem and research questions are formulated. Finally, the purpose, deposition, and delimitation of the thesis are presented.
1.1 Background
1.1.1 Changing Supply Chain Environment
Recently, supply chain management faces a number of new challenges due to the changing international and domestic market (Wolf, 2011). The business trends are moving towards complex supply networks (Harland, Brenchley, and Walker, 2003). The fundamental aspects influencing this direction are related to cost, price, quality, and delivery service of offerings. Globalization and changes in the world events have resulted to the changes in supply chain environment (Giunipero and Eltantaxy, 2004). The moving towards leaner supply chain and just-in-time delivery is seen as the opportunity for growth
(Peck, et al., 2003). Many in-house activities have been shifted to other places in order to concentrate on one’s own core activities and gain advantages from outsourcing. Several alternative suppliers are used giving the benefits in terms of flexibility and low cost in some cases (Jonsson, 2008). However, when low cost is pursued, the need of high quality and precise delivery might not be ensured. Over fifty per cent of the cost of goods sold may be counted from the costs of raw materials and components purchased as input goods (Jonsson, 2008). Instead, it leads to another direction moving towards partnership relations by reducing the number of supplier for more
systematic and cost-effective supply structure. The potential and appropriate supply structures should be highly considered as the result.
1.1.2 The Focus on How to Manage Company Risk
The word, risk is commonly defined as the probability of loss (Mitchell, 1995). Following the view of Yates and Stone (1992 as cited in Mitchell, 1995; Zsidisin, 2003), on risk, it is the compression of three elements blended: 1) variance of outcomes or potential of loss: resulted in various degree
of loss, number of loss, multiple categories or type of loss),
2) significance of loss: significance of potential losses in a situation, and 3) uncertainty: degree of confidence for developing risk assessments to
variance of outcomes or potential of loss and significance of loss)
The type of loss can be caused by different risk situations, which in turn, a situation can also lead to several types of loss (Harland, Brenchley, and Walker, 2003). The categorization of losses was developed by Jacoby and Kaplan in 1972 and Roselius in 1971 as cited in Mitchell (1995) and Harland, Brenchley, and Walker (2003), the types of loss are: financial loss, performance loss, physical loss, psychological loss, social loss, and time loss.
By following several trends in supply chain environment, increases in the degree of involvements, speed, and flexibility bring the company the agility and leanness. The probability to be interrupted and lead to the different types and degree of loss is increasing. This can be seen that the advantages always come with risks which need to be managed by the company. How previous experiences were managed can guide the company to develop capability. For instance, the notable incidents are related to the protests, terrorists (e.g. 9/11 attack), disease (e.g. SARS virus, foot and mouth disease), political crisis,
sluggish economy, natural disasters (e.g. flood, earthquake, hurricane, tsunami), human errors, and war (Giunipero and Eltantawy, 2004; Jüttner, 2005; Tang, 2006; Sarkar and Mohapatra, 2009; Norrman and Jansson, 2004; Stecke and Kumar, 2009). According to Mitchell (1995) and Norrman and Jansson (2004), the risk comprises of probability multiplied impact of loss. The significance of loss tends to gain more attention of the managers rather than the probability of loss (Harland, Brenchley, and Walker, 2003) which finally drive the company to protect the business against significance of loss by managing and being aware of risk.
1.1.3 Supply Chain Integration
As the competition between organizations transforms into the competition among different supply chains (Christopher, 2011), many companies are looking for the supports those can strengthen their competitiveness. Cooper, Lambert, and Pagh (1997) indicated that integrations of internal functions and external organizations are definitely required in order to improve the performance. Although there is no uniform definition of supply chain integration (SCI), many researchers agree that integration is an indispensable part of Supply Chain Management (SCM) which can be defined as:
“The systemic, strategic coordination of the traditional business functions and the tactics across these business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long-term performance of the individual companies and the supply chain
as a whole.”(Mentzer, et al., 2001, p.18)
In order to adapt to different situations, the layers of integration that company chooses may be different. Fabbe-Costes and Jahre (2007, p.839) defined four
layers of integration, including “integration of flows (physical, information, financial), integration of processes and activities, integration of technologies and systems, and integration of actors (structures and organizations)”. In general, integrated supply chain can bring a series of benefits for the organization. It can help to improve performance such as faster inventory turnover and quick response to customers (Fabbe-Costes and Jahre, 2007; Forslund and Jonsson, 2007; Lee, 2006), gain sustainable products, information, services, and capital flows (Wolf, 2011), develop operational solutions (Kobayashi, Tamaki, and Komoda, 2003), develop controlling tools
(Seuring, 2006), create customer value (Cooper, Lambert, and Pagh, 1997), and manage key business processes across supply members (Lambert, et al., 1998; Croxton, et al., 2001).
1.1.4 Supplier Information Integration
Among the different layers of integration mentioned above, the information integration was paid more attention because of the frequency of use and the importance to the matters. Prajogo and Olhager (2012) proposed the definition and purpose of information integration:
“Information integration refers to the sharing of key information along the supply chain network which is enabled by information technology (IT). One of the main purposes of information integration is to achieve real-time transmission and processing of information required for supply chain
decision making” (Prajogo and Olhager, 2012, p.514).
Supplier integration, just as its name implies, is a state of cooperation activities with suppliers, from purchasing to production of an organization
SCI, in order to help manufacturers and their suppliers to establish common goals and support each other by operational processes (Bowersox, Closs, and Cooper, 2010;So and Sun, 2010).
In this thesis, we will focus on the information integration in supplier’s side, which is named as supplier information integration (SII). It refers to all the information sharing activities through using information technology with the supplier and/or supplier’s supplier.
1.2 Problem Discussion
1.2.1 The View on China and Thailand
China and Thailand are two countries located in east side of Asia continent having common border countries: Myanmar and Laos. The total population of both countries is over 1.4 billion, with China accounting for 95% of this population (CIA, 2012). Both China and Thailand are currently considered in the group of Newly Industrialized Countries (NICs) (WTO, 2008; Asian Development Bank, 2009). The Gross Domestic Products (GDP) of China and Thailand are mainly accounted for industrial sector (CIA, 2012) in which the manufacturing value added (% of GDP) is 30 for China and 36 for Thailand (World Bank, 2011b). The GDP per capita of China and Thailand are close, which are $8,400 and $9,700 respectively (CIA, 2012). While China is at 91st, Thailand is 17th ranked among other developed countries that have the most business friendly regulation reflecting to the ease of doing business (World Bank, 2012). However, both countries are gradually downgraded from the previous years.
1.2.2 Supply Risk and SII in Manufacturing Industry
In business, different trends such as globalization, outsourcing, increased competition between different supply chains, reduction of supplier base, and leanness have created the supply chain in rapid change to higher risk exposure (Christopher, et al., 2002 as cited in Christopher and Lee, 2004; Harland, Brenchley, and Walker, 2003; Norrman and Jansson, 2004; Paulsson, 2007). By this, it has been increasingly discussed to the importance of supply and demand as the two different issues of supply chain management. Although, the supply side has been considered as easier to control than demand (Ekwall, 2009), most of the studies had stressed on the perspective of an individual company with higher percentage of interest on supply side over the demand side (Paulsson, 2004). This can convey to one opinion that the problems those are experienced at the supply side is greater in case of the number, probability and consequence, than what experienced at the demand side (Paulsson, 2004; 2007).
As concerning in the manufacturing industry, the complexity of supply networks can be reflected from the number of interactions and variant of source. The benefits of having many suppliers are negotiating advantages, lower cost of supplier relation, and capacity flexibility (Jonsson, 2008). Nevertheless, many companies are still striving for other aspects by enhancing partnership relation. By this, small number of suppliers at short distance is considering in order to efficiently transfer highest value among each party. The expected outcomes are lowest overall cost of goods sold, better quality of offerings, less delivery variation, and collaborative product development (Jonsson, 2008). However, the low number of interaction and variant of source might still lead to the other risks due to the high dependency and tight relationship with fewer suppliers. This is also stressed by Paulsson
(2004) that the opportunities come with risks when the dependency is higher in the supply chain.
Manufacturing firms may involve their suppliers’ operations in order to meet their expectation (Li, et al., 2007). Suppliers are increasingly seen as the important resources for manufacturers in a competitive environment that have large and direct impact on cost, quality, technology, and time-to-market of new products (Handfield, et al., 1999; Krause, et al., 2007). The result is that manufacturing firms might rely increasingly on their suppliers. According to
Handfield, et al. (2000), 50 per cent to 60 per cent of the total revenue in manufacturing firms is accounted by the procurement costs for raw materials and components. Since this kind of dependency cannot be eliminated, it means that the supply risk will come on its heels.
Meanwhile, in order to improve the performance, SII might be implemented by the companies. Many studies have proved how supplier information integration can actually bring beneficial results. For example, Sheu, Yen, and Chae (2006) indicated that better IT capabilities and better communication can lead a better platform for coordinating, participating, and problem solving. However, this later leads to a suspicious notice whether the implementation of supplier information integration can actually be the protection against risks from supply side.
1.2.3 The Link to Research Questions
The view of this thesis is focusing on the manufacturing industries in China and Thailand. The manufacturing industry is seen as having an important role contributed to the GDP of both countries.
To protect against risk of dependency from supply side, transparency between supply chain members is needed through the flow of information. Generally, the term integration in supply chain management is referred to the beneficial purposes such as enhanced market performance and customer satisfaction (Swink, Narasimhan, and Wang, 2005) which then accelerate the business. However, the speed of business is coordinating to the risk and uncertainty exposed to the companies. There is a belief that leanness could possibly limit the opportunities to expand business in term of dynamics of industry and strategic change (Peck, et al., 2003). Therefore, it comes to the link of this thesis to the research questions whether supplier information integration does reduce supply risks or it is just a beneficial mechanism that merely leads to leanness and success of information sharing with suppliers. For answering this question, extended supplier information integration for supply risk protection is chosen as our research scope based on the perspective of focal company (Figure 1). In addition, the answer is aimed to demonstrate the similarities or differences between China and Thailand which can convey to the new knowledge or theory for further research at the end of the thesis.
1.3 Research Question
RQ1: How does the supplier information integration reduce supply risks in Chinese manufacturing industry?
RQ2: How does the supplier information integration reduce supply risks in Thai manufacturing industry?
RQ3: What is the difference between Chinese and Thai manufacturing industries in terms of the supplier information integration for reducing supply risks?
1.4 Purpose
The purpose of this thesis is to contribute to a deeper understanding of supplier information integration for mitigating supply risk in Chinese and Thai manufacturing industries. This thesis attempts to find, describe, and compare the significant relationship between supplier information integration and supply risk in Chinese and Thai manufacturing industry.
1.5 Thesis Deposition
The thesis deposition illustrates the overall picture of the thesis (Figure 2). The introduction gives the background of the thesis in order to formulate the research methodology which guides the research process; the theory chapter connected research questions to the concepts. The generation of hypothesis which is the sprout of methodology and theories demonstrates how the empirical finding can be linked to the answer of research questions. Further, empirical data was explained and analyzed for testing the hypotheses. Finally, the research questions are answered in the conclusion.
1.6 Delimitation
There is a large number of articles focuses on supplier integration which includes a state of cooperation activities with suppliers, from purchasing to production of an organization (Das, Narasimhan, and Talluri, 2006). Therefore, we wanted to investigate whether supplier integration could be a major instrument for the purpose of supply risk deduction in Chinese and Thai manufacturing industries. However, due to the time constraint and boarder scope of supplier integration, we had identified and discussed for the most interesting subject and finally came up with the supplier information integration for mitigating supply risk. Nevertheless, this subject was still rarely found in the literatures which finally limited our theoretical exploration.
Philosophies Approaches Strategies Choices Time Horizons Techniques and Procedures Positivism Pragmatism Interpretivism Realism Deductive Inductive Experiment Survey Case Study Action Research Grounded Theory Ethnography Archival Research Mono Method Mixed Methods Multi-Method Cross-Sectional Longitudinal Data Collection and Data Analysis
Figure 3: The research “onion”
Source: Mark Saunders, Philip Lewis and Adrian Thornhill 2008(as cited by Saunders,
Lewis, and Thornhill, 2009, p.108)
2. Research Methodology
his chapter presents the methodological design of the thesis. It outlines the research philosophies, approaches, strategies, choices, time horizons, techniques and procedures based on the literature review and appropriateness for this research.
The research methodology part of this thesis is guided by “the research onion model” from Saunders, Lewis, and Thornhill (2009, p.108) in which the issues related to the choice of data collection techniques for a thesis are underlying separately in each layers of the onion.
Furthermore, there are two headings added apart from the research onion. The first heading is research credibility which aims to ensure the quality of the thesis. The second heading is summary of research methodology which ends Chapter 2 by demonstrating the summary overview of this section.
2.1 Research Philosophies
According to Saunders, Lewis, and Thornhill (2009), research philosophy is arching of the development of knowledge and the nature of that knowledge. There are four research philosophies: positivism, realism, interpretivism, and
pragmatism.
Positivism is a strict scientific method and approach that endorse the stance
of natural sciences (Saunders, Lewis, and Thornhill, 2009). Researcher who is working in this tradition may prefer to work “with an observable social
reality and that the end product of such research can be law-like generalizations similar to those produced by the physical and natural
scientists” (Remenyi, et al., 1998, p.32). The belief of realism is the reality
that is independent of human mind and frequently contrasted with idealism
(Saunders, Lewis, and Thornhill, 2009). Comparing with a strict method adopted by positivist, interpretivism proposes that the subjective aspects should be considered in the research. According to Saunders, Lewis, and Thornhill (2009), the term “social actors” is important since it is a basis for interpreting social roles and differences between humans. Pragmatism emphases the importance of research question and practice; it argues that it is a more proper way to answer those questions (Saunders, Lewis, and Thornhill, 2009).
Research philosophy for this thesis
In this thesis, the authors adopted the positivism since our research design was based on existing theories in the field of supply risk and supplier information integration. The application and production of knowledge were aiming to derive from the thesis. In addition, the final findings were explored from the data collection in order to response to the research questions.
2.2 Research Approaches
According to Saunders, Lewis, and Thornhill (2009), there are two main research approaches: deduction (testing theory) and induction (building theory).
Deduction - Testing Theory
Saunders, Lewis, and Thornhill (2009) indicate that deduction is regarded as a scientific research. Researcher who applies a deductive approach needs to build the hypothesis from existing knowledge and theory and present how to test the hypothesis (Ghauri and Gronhaug, 2005). Robson (2002) proposes the following five sequential stages used in deductive research:
Stage1: deducing a hypothesis from the theory;
Stage2: expressing the hypothesis in operational terms, which proposes a relationship between two specific concepts or variables;
Stage3: testing this operational hypothesis;
Stage4: examining the specific outcome of the inquiry;
Induction -Building Theory
Inductive approach refers to the process of collecting data and developing theory through data analysis (Saunders, Lewis, and Thornhill, 2009). By using an inductive approach, theory is an outcome instead of basis; the process started from observation to finding, and ended at theory building
(Ghauri and Gronhaug, 2005).
Saunders, Lewis, and Thornhill (2009) summarized some major differences between deductive and inductive approaches to research showing in Table 1.
Table 1: Major differences between deductive and inductive approaches to the research
Source: Saunders, Lewis, and Thornhill (2009, p. 127)
Research approach for this thesis
The research approach for this thesis was deductive since the hypotheses were built on the basis of existing theories. The theoretical framework was structured based on theories those were relevant to supply risk, supplier information integration and so on. Some researchers think that deductive and
inductive approaches are not absolutely separated from each other and they can be used at the same time (Ghauri and Gronhaug, 2005). Therefore, we were expecting to forecast or propose the new theoretical contribution from this thesis.
2.3 Research Strategies
Saunders, Lewis, and Thornhill (2009) enumerate and present a number of different research strategies: experiment, survey, case study, action research, grounded theory, ethnography, and archival research.
Survey
Survey is usually used along with the deductive approach (Saunders, Lewis, and Thornhill, 2009). It is a common research strategy for gathering information by asking questions in business and management research
(Graziano and Raulin, 2010; Saunders, Lewis, and Thornhill, 2009). The survey strategy allows the researcher to collect plentiful data from a large population in a low cost way (Saunders, Lewis, and Thornhill, 2009).
The clear planning is important to the success of a survey. Graziano and Raulin (2010) summarized the following main steps in survey strategy which needs to work cautiously in each step:
Determine what area of information is to be sought; Define the population to be studied;
Decide how the survey is to be administered;
Construct the first draft of the survey instrument; edit and refine the draft; Pretest the survey with a subsample; refine it further;
Administer the final form of the instrument to the sample; Analyze, interpret, and communicate the results.
Graziano and Raulin (2010) also describe two types of surveys: status survey and survey research. Status survey presents the current characteristics of a population while survey research focuses on discovering relationships among variables. There are some common survey instruments that can be used in the research: (1) questionnaire, respondents answer certain questions by writing or marking; (2) interview schedule, refers to interviews by telephone or in-person. Saunders, Lewis, and Thornhill (2009) suggest observation that is another important and frequently used instrument associated to the organization and methodological research. All of these instruments require a clear guide and understandable questions for respondents.
In designing the questionnaire, two types of questionnaire are mostly found: open and closed questions (Saunders, Lewis, and Thornhill, 2009). Open question refers to the type of question that allows the respondents to freely answer while closed question refers to the question that limits the way the respondents to answer. According to Saunders, Lewis, and Thornhill (2009), six types of closed question are highlighted: list, category, ranking, rating, quantity, and matrix.
According to Keller, et al. (2002), the process of scale development in rating questions can affect the qualities measure of the research. This was related to the validity and reliability of the responses which were finely answered according to the seven rating –scale. In the study of Keller, et al. (2002), 36 articles out of 75 articles used 7-point Likert scale as the Likert-style rating scale in Information Sharing Processes and Technology, which was the most commonly used among the researchers in this subject.
Research strategy for this thesis
This thesis aimed to find the relationship between supply risk and supplier information integration. According to Saunders, Lewis, and Thornhill (2009), survey strategy is normally used for seeking particular relationships between variables and producing models of these relationships. Therefore, the survey strategy was chosen for this thesis.
Survey strategy
1. The information about supplier information integration and supply risks were sought
2. The manufacturing listed companies in China and Thailand were defined as the population we studied. 3. Questionnaire was used as the instrument for the survey
(Appendix I).
4. Constructed the questionnaire, edited according to the suggestions from tutor and examiner.
5. The questionnaire was sent out to some manufacturing companies to pretest and refined it.
6. Drew the representative sample and sent out the questionnaire.
7. Analyzed, interpreted, and communicated the results. Questionnaire
design
1. Open question: working position of respondents and other specific information about information technology and information sharing
2. Closed question:
(a) List question: host country
(b) Category question: how long the respondents were working with the companies
(c) Rating questions: the opinion data about supplier information integration and supply risks.
Scale for rating
question 7-point Likert scale
Table 2: Research strategy for this thesis
In this thesis, we used questionnaire as the instrument for collecting information, and we followed the respondent by telephone call. Both open
question and closed question were used as showing in the Table 2. The type of rating was designed in term of agreement through the category, 7-point Likert scale.
2.4 Research Choices
According to Saunders, Lewis, and Thornhill (2009), research choice refers to the way to combine data collection techniques and analysis procedures those can be expressed in four types of method (Figure 4): mono method, multiple methods, and mixed methods.
Mono method can be referred as a durable package combining a single data collection technique with a compatible specific analysis procedure. For instance, questionnaire is used as a quantitative data collection technique and analyzed through statistic terms such as graphs.
Multi-method can be referred as a multi package combining data collection techniques associated to the analysis techniques. The combination is restricted only for the techniques those are in the same family within either quantitative or qualitative method. For instance, questionnaire and structured observation are used as the quantitative data collection techniques and analyzed through statistical procedures.
Mixed method can be referred as a customized package freely combined different data collection techniques and analysis procedures in a research design. However, in mix-method research, the analysis procedures are separately used either in parallel or sequential depending to each associated type of data collection techniques. For instance, questionnaire and interview are used as two different types of data collection techniques. Questionnaire is analyzed through statistical procedures either at the same time or after the
analysis of interview by categorizing. In another case, both quantitative and qualitative approaches are combined at some other stages. This leads to the merging process to “qualitie” numerical codes to narrative or “quantitise” narrative to numerical codes (Saunders, Lewis, and Thornhill, 2009).
Research choice of this thesis
The research choice of this thesis was mono method using only a single quantitative data collection technique.
The attempt was to collect primary data through the use of questionnaire which was later summarized and analyzed in statistical procedures. The questionnaires were distributed to the respondents through electronic engines. The phone call was used for questionnaire interviews accelerated the response rate in some cases. In addition, the secondary data was used as a knowledge base in literatures and theoretical frameworks those derived through different types of source. The main sources of secondary data collection were Linnaeus University’s library and LNU’s search engines through dissertations search and databases such as Emerald and Google Scholar.
Research Choices
Mono Method Multiple Methods
Multi-Method Mix-Method Multi-Method Quantitative Studies Multi-Method Qualitative Studies Multi-Model Research Mix-Method Research
Figure 4: Research choices
2.5 Time Horizons
According to Saunders, Lewis, and Thornhill (2009), the research can be planned to conduct in two ways: cross-sectional and longitudinal studies. Cross-sectional studies are time constrained studies those are taken individually or together at a particular time while longitudinal studies are taken individually or together over the period of time in order to demonstrate the trend or changes.
Time horizon of this thesis
The time horizon of this thesis was only cross-sectional which the observation was conducted once at a certain moment of time. The findings were used at once for evaluating and analyzing relationship of studied variables based on a significant purpose.
2.6 Data Collection and Data Analysis
As it mentioned in the Research Strategies part, survey and questionnaire were chosen as strategy and instrument respectively for collecting data in this thesis.
2.6.1 Population and Sampling
According to Bryman and Bell (2007, p.182), the population refers to “the universe of units from which the sample is to be selected” while the sample is “the segment of the population that is selected for investigation”. Saunders, Lewis, and Thornhill (2009) summarized different sampling techniques (Figure 5). There are two types of sampling techniques; probability and non-probability. The chance to select each case is usually equal and known by using probability sampling while some other cases might be likely to be
selected under non-probability samplings when the probability is unknown (Bryman and Bell, 2007; Saunders, Lewis, and Thornhill, 2009).
Figure 5: Sampling techniques
Source: Saunders, Lewis, and Thornhill, 2009, p.213
Bryman and Bell (2007) argued that sample can reflect the population more accurately and sampling error can be kept in a minimum level under the probability sampling, rather than non- probability sampling. While many researchers are concerned about the sample size, Bryman and Bell (2007)
argued that the absolute size of sample is important, not relative size meanwhile they agree that an increasing sample size might decrease the sampling error. Saunders, Lewis, and Thornhill (2009) claimed that an absolute sample size of 30 or more will result to a normal distribution.
The population we studied was the manufacturing listed companies in China and Thailand. We used simple random sampling method and drawn the sampling frame based on the list of listed companies from The Stock Exchange of Thailand (www.set.or.th) (2012) and Shenzhen Stock Exchange
(www.szse.cn ) (2012). When conducting the phone call, we found that some companies were not valid to the study as they had no production at that moment. The sampling frame had been adjusted after that. However, the adjusted number was very small as counted around 3% out of the previous sample frame. Thus, the sample frame was shown after adjusted as 955 companies in China and 221 companies in Thailand.
The respondents were firstly contacted by phone before sending the questionnaire both in soft files and electronic link to their e-mail addresses. The reminder e-mails were sent out twice after a long holiday and one day before the deadline of conducting the survey. Finally, we got 159 responses from China and 40 responses from Thailand with the response rate of 16.65% from Chinese manufacturers and 20.81% from Thai manufacturers. Concerning to the response rate, in total, the response rate from China and Thailand was 20.81% which was acceptable. As cited by Forslund and Jonsson (2010), the response rates from mail survey are often received as 20% and as low as 10%.
The distribution of respondents in term of industrial sector is shown in Table 3; the distribution of respondents in term of work years is shown in Table 4.
Country Sector No. of Firm No. of Respondent Response Rate
Food & Beverage 54 5 9.26%
Textiles & Apparel 45 10 22.22% Timber & Furnishings 9 5 55.56%
Paper & Printing 29 8 27.59%
China Electronics 110 40 36.36% Metals & Non-metals 115 16 13.91%
Machinery 312 52 16.67%
Pharmaceuticals 87 4 4.60%
Others 20 3 15.00%
Total 955 159 16.65%
Thailand
Food & Beverage 45 4 8.89%
Textiles & Apparel 28 6 21.43%
Timber & Furnishings 3 1 33.33%
Paper & Printing 3 0 0.00%
Petrochemicals 24 1 4.17%
Electronics 19 5 26.32%
Metals & Non-metals 36 6 16.67%
Machinery 53 21 39.62%
Pharmaceuticals 4 0 0.00%
Others 6 2 33.33%
Total All industries 221 46 20.81%
Table 3: Distribution of the sampling frame and the respondents
Nation Work Year Frequency Percent Valid Percent Cumulative Percent
China
Less than 1 year 9 5.7 5.7 5.7
1-2 years 38 23.9 23.9 29.6 3-5 years 66 41.5 41.5 71.1 6-10 years 30 18.9 18.9 89.9 Over 10 years 16 10.1 10.1 100.0 Total 159 100.0 100.0 100.0 Thailand
Less than 1 year 3 6.5 6.5 6.5
1-2 years 8 17.4 17.4 23.9
3-5 years 9 19.6 19.6 43.5
6-10 years 12 26.1 26.1 69.6
Over 10 years 14 30.4 30.4 100.0
Total 46 100.0 100.0 100.0
Table 4: Distribution of work year from the respondents
2.6.2 Translation and Transformation
Given our constraints with respect to official language in China and Thailand, the questionnaire distributed in China was translated to Chinese, while the
questionnaire distributed in Thailand was sent out in both English and Thai. The responses were translated after receiving in order to improve the validity of our research. The completed questionnaires were checked, edited, coded, grouped, and transformed to Excel for using in SPSS.
2.6.3 Data analysis
Bryman and Bell (2007) introduced three types of quantitative data analysis: (1) univariate analysis which analyzes only one variable at a time; (2) bivariate analysis which two variables and their relationship at a time; (3) multivariate analysis which refers to the analysis of three or more variables. In interpretation of output from correlations, Pallant (2010, p.133-134)
suggested to:
1) Check the number of sample
2) Determine the direction of relationship by following positive or negative sign in front of the correlation coefficient value (r) conformingly to the same direction of the result
3) Determine the strength of the relationship as weak when r = 0.1 to 0.29, medium when r = 0.3 to 0.49, and large when r = 0.5 to 1
4) Calculate the coefficient of determination by putting the square for r value and converting to percentage by multiplying 100
5) Assess the significance level (p) for indicating the confidence of the result when p<0.05 level.
Data analysis for this thesis
In this thesis, the authors defined the supply risk as the dependent variables and the supplier information integration as the independent variables. Therefore, bivariate analysis was applied in this thesis. Pearson Correlation
which is appropriated for analyzing interval level continuous variables
(Pallant, 2010), was chosen as the main techniques to analyze the data collected. Each independent variable in Supplier Information Integration (information technology and information sharing) was paired with each dependent variable (supply risk, probability of risk, and impacts of risk) in order to test the relationship in Bivariate Pearson Correlations. Therefore, there were nine correlations tables derived after running the SPSS showing separately under correlations in Chinese and Thai manufacturing industries (shown in Appendix III and Appendix V). In addition, reliability analysis and descriptive statistics were used to check the reliability of the questionnaire and describe all variables.
2.7 Research Credibility
According to Saunders, Lewis, and Thornhill (2009, p.156), the credibility of research findings is enhanced by “reducing the possibility of getting the answer wrong” through emphasizing reliability and validity on the research design. Reliability and validity are regarded as the necessary instrument to test the results from the survey (Burton and Mazerolle, 2011).
2.7.1 Validity
Validity refers to the compatibility of relationship between variables on findings (Saunders, Lewis, and Thornhill, 2009). It is concerned with the instrument chosen that can measure the study (Burton and Mazerolle, 2011).
There are four criteria of validity: face validity, content validity, construct validity and criterion validity. Face and content validity are qualitative measures of validity and the first steps to establish validity. They are often employed in survey through judging the appearance, relevance and
representativeness of a survey by experts with expertise in related area.
(Burton and Mazerolle, 2011). Criterion validity refers to whether it is consistent with previous and valid instrument or some other criterion. Construct validity aims to test whether survey demonstrate what is intended to measure (Burton and Mazerolle, 2011).
Validity of this thesis
In this thesis, face and content validity were established in order to ensure the appearance, relevance and representativeness of the survey. It carried out among different individuals included the tutor and examiner who are experts in this area. At the same time, the survey was also pretested with persons who were working in purchasing department in Chinese and Thai manufacturing companies. Due to the lack of relevant literature and research, the comparison between this survey and previous research could not be achieved. However the survey were designed based on relevant theories and checked by experts, the instrument used was achieved the requirement to measure the intended issues.
2.7.2 Reliability
Reliability can refer to the consistency or repeatability of the findings in a way the data collection techniques are taken. Easterby-Smith, et al. (2008 as cited in Saunders, Lewis, and Thornhill, 2009) give three questions for assessing validity:
1) Will the measures yield the same results on other occasions? 2) Will similar observations be reached by other observers?
Reliability of this thesis
The survey was send to the persons who was in the related field in manufacturing companies in China and Thailand. The collected responses were checked, translated, transformed, and edited as soon as possible in order to ensure the reliability. At the same time, all the secondary data was collected from reliable sources such as the journals, textbooks, and publications.
2.8 Summary of Research Methodology
Onion Layers Layers of Thesis's Methodology
Research Philosophies Positivism
Research Approaches Deduction
Research Strategies Survey
Research Choices Single quantitative data collection technique
Time Horizons Cross-sectional
Data Collection and data analysis
Population Manufacturing listed companies in China and Thailand
Sampling Simple random sampling
Data analysis Person correlation, reliability analysis
Research credibility
Validity Face and content validity
Reliability
Data collection process and the use of secondary data
were strictly conducted Table 5: Summary of research methodology of this thesis
3. Theory
his chapter presents all the theories that are relevant to the thesis. The section begins with the link of research questions to the concepts: supplier information integration, followed by risk, and ended with macro environments in China and Thailand. All theories and relevant concepts are linked to the generation of hypotheses in Chapter 4 in order to answer the research questions at the end of the thesis.
Table 6 shows the research questions and respective theories introduced in this chapter.
Research Question Respective Theory Chapter
1: How does the supplier information integration reduce supply risks in Chinese manufacturing industry?
3.1 Supplier Information Integration 3.2 Supply Risk
3.3.1 Macro Environments in China 2: How does the supplier information
integration reduce supply risks in Thai manufacturing industry?
3.1 Supplier Information Integration 3.2 Supply Risk
3.3.2Macro Environments in Thailand
3: What is the difference between Chinese and Thai manufacturing industries in terms of the supplier information integration for reducing supply risks?
3.1 Supplier Information Integration 3.2 Supply Risk
3.3 Macro Environments in China and Thailand
Table 6: Research questions and respective theories
T
3.1 Supplier Information Integration
3.1.1 Introduction of Supplier Information Integration
Recently, both researchers and company managers pay attentions to supply chain integration. Awad and Nassar (2010) proposed the following factors as the main causes of this trend: (1) manufacturing industry may be influent by a global environment (such as global standard for product); (2) an inevitable trend for developing and operating manufacturing systems in a environmental way; (3) the business and organizational structures for manufacturing operation are more stressful.
According to different flows, SCI is sorted into financial flow integration, physical flow integration, and information flow integration (Zolait, et al., 2010). Prajogo and Olhager (2012) classified the corresponding integration activities into two forms: logistics integration and information integration. Logistics integration refers to practices and activities of coordinating the flows of materials and goods from upstream to downstream while the information integration represents the use of information technology and sharing key information along the supply chain network (Prajogo and Olhager, 2012). It is demonstrated that both of these integrations can help the firms to improve their performance (Zolait, et al., 2010); meanwhile the intensity of information integration has a positive relationship with logistics integration (Prajogo and Olhager, 2012).
As SII has been defined in the background, it refers to all the information sharing activities with the supplier, and/or supplier’s supplier by using information technology. The purpose of supplier information integration is to timely and accurately transmit information required for supply chain decision making (Prajogo and Olhager, 2012), and to achieve the goal of cutting cost
down through reductions of inventories (Lee, So, and Tang, 2000). It is indicated that information integration can be a major strategy to eliminate the “bullwhip effect” (Yu, Yan, and Cheng, 2001), and eventually leads both the firm and total supply chain to better performance (Yu, Yan, and Cheng, 2001; Palsson and Johansson, 2009; Zolait, et al., 2010) and it becomes necessary to improve the effectiveness of the supply chain (Zolait, et al., 2010).
Prajogo and Olhager (2012) summarized two major aspects of information integration: information technology and information sharing. The former refers to the technical aspects and stresses the importance of adopting e-business technologies as means for SII; while the latter presents the social aspects and focuses on the communication with suppliers. Both of them are indispensable, companies should be capable of building both information technology and information sharing aspects for the sake of maximum benefits from information integration (Fawcett, et al., 2007).
3.1.2 Information Technology
According to Handfield and Nichols (1999, p.15), Information technology
“encompasses the information that businesses create and use as well as a wide spectrum of increasingly convergent and linked technologies that process that information”.
Information (and communication) technology plays a vital and irreplaceable role in SII (Prajogo and Olhager, 2012). First, IT provides the basic platform to communicate and coordinate between a focal company and supplier in order to create a virtual and agile supply chain (Bagchi and Shjoett-Larsen, 2002; Li, et al., 2006; Prajogo and Olhager, 2012); Second, an effective and reliable IT system can provide the way of timely, accurate, and efficient
supply chain information exchanging among supply chain partners, such as inventory level, delivery status, and production planning and scheduling (Bagchi and Shjoett-Larsen, 2002; Prajogo and Olhager, 2012). Third, IT can support and control key processes and activities in supply chain, such as sourcing, procurement, and order fulfillment (Prajogo and Olhager, 2012).
Forth, Effective IT connection can improve the integration between supply chain partners, improve their performance and make the physical flows seamless (Soliman and Youssef, 2001; Carr and Kaynak, 2007).
There are many approaches and technologies used for the information integration, such as Electronic Data Interchange (EDI) systems, Extensible Markup Language (XML), and so on (Awad and Nassar, 2010). In order to realize the presence of information integration, the focal company and suppliers should try to use compatible systems and procedures (Bagchi and Shjoett-Larsen, 2002). They should understand the meaning of the data from each others; the definition and usage of same data item must be consistent across supply chain partners (Awad and Nassar, 2010; Carr and Kaynak, 2007) categorized information technology used for business into two groups: traditional information technology and advanced information technology.
Traditional information technology refer to the use of telephone, fax, electronic mail, written, and face-to-face contact while advanced information technologies include computer-to-computer links, electronic data interchange (EDI), and enterprise resource planning (ERP) (Carr and Kaynak, 2007). Although traditional information technologies are not so systematic, it is considered as an important medium which provide additional opportunities to share information for information exchange, and cannot be replaced by advanced information technologies (Wognum et al., 2002 as cited by Carr
and Kaynak, 2007). Carr and Kaynak (2007) indicated that the use of telephone, fax, electronic mail, fax, computer-to-computer links, EDI and ERP provide a broader and deeper accessible information and more frequent communication about business activities. For example, by using electronic data interchange (EDI) technology, timely and accurate information exchange among supply chain partner is facilitated (Bagchi and Shjoett-Larsen, 2002; Carr and Kaynak, 2007).
Except the technologies mentioned above, information sharing is also embedded into popular used of other supply chain strategies such as Quick Response (QR), Vendor Managed Inventory (VMI) and Continuous Replenishment Programs (CRP) etc.(Lee, So, and Tang, 2000; Li, et al., 2006).
Bagchi and Shjoett-Larsen (2002) summarized three stages of IT integration according the using of following perspectives: (1) transaction systems, (2) communication systems, internet/ extranet, (3) bar-coding and track- and-trace systems, electronic POS (point-of-sale), and (4) vendor managed inventory (VMI), collaborate planning, forecasting and replenishment (CPFR), customer relationship management (CRM). They classified low IT integration as the company which relies on fax/phone, legacy systems and limited email/internet use for communication with their partners. In contrast, a company that extensively uses ERP, SCP, EDI, XML and bar coding for communication is regarded as in the stage of high integration.
Stages of Information Integration
Supply Chain
Integration Using Low Integration Medium Integration High Integration
Transaction Systems MRP II systems, legacy systems ERP systems Intra-Company Rigid interfaces Value: Mechanization of existing process
ERP and Supply Chain Planning(SCP) systems Inter-company integration Flexible interfaces Value: Process improvement Communication Systems, Internet/ Extranet Emai/Fax/Phone Internet/ Extranet only used for limited purpose
Few EDI/ Internet links to customers/ Suppliers Extranet
Extensive use of EDI/ Internet/XML links within supply chain Bar-coding and Track-
and-trace Systems, Electronic POS (point-of-sale)
Data Capture, Inventory Visibility
Only bar-coding of finished products Track- and-trace Systems and Electronic POS
More extensive bar-coding, automated email updates and confirmations
Bar-coding from entry to dispatch, Track-and-Trace throughout the SC Key suppliers and customers connected Vendor Managed Inventory(VMI), Collaborate Planning, Forecasting and Replenishment(CPFR), Customer Relationship Management(CRM)
Not used Experimental stage with
one or a few suppliers/customers
Strategic suppliers have access to production plans, materials requirements, sales forecasts and orders
Table 7: Stages of information integration
Source: Bagchi and Shjoett-Larsen, (2002, p.100)
3.1.3 Information Sharing
According to Lee, Kwon, and Severance (2007), supplier linkage is one of the most essential linkages for information sharing in supply chain. When compared with information technology which can be regarded metaphorically as intermediary, information sharing concentrates on the willingness and content of SII. In order to make the information technology plays in a role, information sharing activities are crucial to support the IT system. According to Carr and Kaynak (2007, p.349),
“Information sharing between the firms refers to information shared between a buyer and key suppliers that is detailed enough, frequent enough, and timely enough to meet a firm’s requirements”.
Information sharing involves the sharing of pertinent knowledge and information among members of supply chain (Bagchi and Shjoett-Larsen, 2002). Information sharing with suppliers requires company to share and exchange not only transactional date, such as materials or product orders
(Prajogo and Olhager, 2012), but also other information with suppliers network including demand, forecast, inventory level and production planning decisions (So and Sun, 2010). Many studies discussed about the type of information shared with suppliers, those are: inventory information (Li, et al., 2005; Kaipia and Hartiala, 2006), production plan and capacities (Li, et al., 2005; Kaipia and Hartiala, 2006; Hsu, et al., 2008), sales information (Lee, So, and Tang, 2000; Lee, Padmanabhan, and Whang, 2004; Li, et al., 2005; Hsu, et al., 2008), demand information (Lee, So, and Tang, 2000; Zhao, Xie and Zhang, 2002; Li, et al., 2005; Kaipia and Hartiala, 2006), order information (Zhao, Xie and Zhang, 2002; Li, et al., 2005;Kaipia and Hartiala, 2006), forecast information (Bagchi and Shjoett-Larsen, 2002;Li, et al., 2005; Kaipia and Hartiala, 2006; Carr and Kaynak, 2007), delivery scheduling data (Bagchi and Shjoett-Larsen, 2002), design and manufacturing data (Bagchi and Shjoett-Larsen, 2002), performance criteria (e.g. production quality data) (Li, et al., 2005), and long-term corporate objectives (Hsu, et al., 2008).
Furthermore, Li, et al. (2005) categorized above information by considering the flow directions: some information sharing activities between a focal company and its suppliers are in two-way communication, such as inventory and production plan sharing; while demand information sharing activities are from downstream companies to their upstream partners, for example, sale information sharing and demand forecasting information; the supply information, for instance order state information, is shared by upstream firms to their downstream partners. Li, et al. (2006) indicated that it is critical for
manufacturing firm to capture and employ timely and accurate supply information, especially when a disruption or adjustment happens at the upstream of supply chain.
A number of studies have demonstrated various benefits of having information sharing with suppliers. Effective information sharing in the supply chains has significant effects on improving performance (Zhao, Xie, and Zhang, 2002; Kaipia and Hartiala, 2006; Hsu, et al., 2008; So and Sun, 2010), managing inventory (Lee, So, and Tang, 2000; Kaipia and Hartiala, 2006; Hsu, et al., 2008), reducing cost (Lee, So, and Tang, 2000;Bagchi and Shjoett-Larsen, 2002), and decision making (Lee, So, and Tang, 2000; Hsu, et al., 2008). Information sharing among the supply chain contributes to create a timely, visible, agile and flexible supply chain (Bagchi and Shjoett-Larsen, 2002;Swafford, et al., 2008;Sezen, 2008; Hsu, et al., 2008). Sharing sales information is viewed as a major strategy to counter the “bullwhip effect” which refers to demand variability amplification from downstream to upstream in supply chain (Lee, Padmanabhan, and Whang, 2004).
Information sharing between a focal company and its key suppliers may also affect service level of suppliers (Kaipia and Hartiala, 2006), as a result the quality of a focal company’s products and relationships with suppliers might be improved (Carr and Kaynak, 2007; Hsu, et al., 2008).
Some studies proposed different level of information sharing. Zhao, Xie and Zhang (2002) defined three levels of information sharing based on the demand forecasts and order information with supplier: no information sharing (NIS), demand information sharing (DIS), and order information sharing (OIS). Li, et al. (2005) classified partial and complete information sharing in terms of level or degree. They indicate that the sharing of demand
distribution and related inventory strategies is regarded as partial information while complete information sharing refer to share more detailed and daily inventory states and daily demand change. Hsu, et al. (2008) used tactical and strategic information to distinguish different levels: purchasing, operation scheduling information are viewed as tactical information while strategic information refers to long-term corporate objectives, marketing and customer information. Five specific indicators to measure the activities of information sharing have also been identified: timeliness, accuracy, adequacy, completeness, and information credibility (Mohr and Sohi, 1995 as cited by Hsu, et al., 2008).
In a word, information technology provides platform of the frequent and timely information sharing, while the information sharing among the members in supply chain determines the content shared.
3.2 Supply Risk
The definition of risk related to business has been discussed for a period of time. The term “risk” can refer to a logical cause and effect relationship as generally mean risk sources and risk consequences (Miller, 1992; Mitchell, 1995; Harland, Brenchley, and Walker, 2003; Jüttner, Peck, and Christopher, 2003; Norrman and Jansson, 2004; Paulsson, 2007; Ekwall, 2009) which uncertainties or negative exposures can lead to the negative outcomes. The concept was expressed in a formula by Mitchell (1995) and Norrman and Jansson (2004) cited at different time frames as Risk = Probability (of the loss of the event) * Impact or significance (of loss of the event). In addition, the common meanings of risk can be expressed in many terms: “(1) a threat or a danger, (2) a probability, (3) the total appraisal of probability and size of the consequence, and (4) a measure of dispersion” (Paulsson, 2007, p.73).
For supply risk, it can be considered as a type of risk based on the exposures and realization of impacts (Harland, Brenchley, and Walker, 2003), a source of risk that is external to the focal company but internal to the supply chain network (Peck, et al., 2003), or a direction of risk towards supply side of an individual company’s point of view (Paulsson, 2007).
Some definitions of supply risk had been prior noticed. Meulbrook (2000 as cited in Harland, Brenchley, and Walker, 2003, p.53) defines supply risk as the “adversely affects inward flow of any type of resource to enable operations to take place; also termed ‘input risk’”. Supply risk can also refer to “the upstream equivalent of the above, it relates to potential or actual disturbances to the flow of product or information emanating within the network, upstream of the focal firm” (Peck, et al., 2003, p.44). According to
Zsidisin (2003), the grounded definition of supply risk is proposed in terms of sources and outcomes as:
“the probability of an incident associated with inbound supply from individual supplier failures or the supply market occurring, in which its outcomes result in the inability of the purchasing firm to meet customer
demand or cause threats to customer life and safety”,(Zsidisin, 2003, p. 222).
The probability of an incident is inter-changeably used with the potential occurrence of an incident (Zsidisin and Ellram, 2003; Zsidisin, et al., 2004)
under the same concepts of probability and impact (Zsidisin, et al., 2004). It is noticed that supply risk is distinguished from other types of risk according to the definitions. It commonly convey to the source of risk occurred in the supply side which negatively affects downstream flows.
