Download Information Quality for the Transformation into Green Supply Chain

IQ for the Transformation into Green SC
Information Quality for the Transformation
into Green Supply Chain: A Case in the Retail
Industry
Completed Research Paper
François de Corbière
École des Mines de Nantes
[email protected]
Johanna Habib
Université de Nantes
[email protected]
Anne-Christine Le Dû
Université de Nantes
[email protected]
Frantz Rowe
Université de Nantes
[email protected]
Hirotoshi Takeda
Université de Nantes
[email protected]
Abstract
This communication investigates the role that information quality (IQ) can play for the transformation of
a Supply Chain into a Green Supply Chain. Green Supply Chain Management is about integrating
environmental concern into the interorganizational partnerships. Today, companies are seeking ways to
meet environmental benefits through CO2 reduction when they operate their supply chain. Information
sharing is key for supply chain performance but the literature on the impact of IQ in Supply Chain
Management is scarce. A case study in the retail industry in France is designed in order to determine the
dimensions of IQ that are critical to ensure a supply chain transformation to develop green just-in-time
delivery. An in-depth qualitative analysis of interviews is conducted including the main supply chain
actors (one retailer, two manufacturers, and one logistics service provider). Our results indicate that the
IQ dimensions that will have significant environmental benefits depends on the type of information
exchanged
Keywords: Environmental benefits, green, information quality, retail, supply chain management.
sigIQ pre-ICIS workshop 2011 1
IQ for the Transformation into Green SC
Introduction
Since Forrester (1958) the reason why organizations should share information across the supply chain
(SC) is no longer a big question mark. Researchers and practitioners all agree that sharing information
about product, demand, and supply will significantly improve the overall economic performance of the SC
(Lambert and Cooper 2000; Lee et al. 1997; Legner and Schemm 2008). Now, researchers have to focus
on which information is shared and how it is shared. Information sharing is all the more important that,
from an environmental viewpoint cooperation across the SC may lead to lower CO2 emissions. Under
societal pressures and anticipating possible goodwill gains, some firms integrate environmental
considerations in the design of their SC (Sadiq et al. 2011; Wang et al. 2011). Following Sarkis, Zhu, & Lai
(2011), we define Green Supply Chain Management (GSCM) as integrating environmental concerns into
the inter-organizational practices of Supply Chain Management (SCM).
In this context the quality of the data and information exchanged is getting recognition as a key success
factor (Chaabane et al. 2008; Hartono et al. 2010; Wiengarten and Humphreys 2010). However, the
actual contribution of information quality (IQ), and especially of the diverse dimensions of IQ, remains
unclear. Our primary research question is thus: How can IQ improve the Green Supply Chain? To answer
this question, we propose to analyze, from different actors’ viewpoints, the contribution of IQ on the
transformation into a green supply chain (GSC). Including various SC actors (retailer, manufacturer, and
logistics service provider), a case study conducted in the retail industry allows deriving some key findings
on logistical processes evolution.
The rest of the paper is organized as follows. The literature on the evolution of SCM is first reviewed. Then
we present the background of IQ as an enabler of the GSC. We then describe the method used for this case
study. Our results indicate that several IQ dimensions concerning a set of critical information enable the
development of GSC. Then these results are finally discussed in the conclusion, in which we explain that
green considerations derive from economic considerations.
Information Quality and Green Supply Chain Management
Evolution of Supply Chain Management
The concept of SCM has emerged as a result of successive organizational changes from “managing its
logistics” towards “managing interdependencies among supply chain actors” (Bowersox et al. 2005). With
respect to an increasing environmental consciousness, the 21st century is definitely about conciliating
economic and environmental benefits; SCM evolution to GSCM is now a reality (Corbett and Klassen
2006; Melville 2010). In this section we examine the conditions and enablers of information sharing and
the specific needs and capabilities of the GSC.
For the purpose of this paper, “a Supply Chain is defined as a set of three or more entities (organizations
or individuals) directly involved in the upstream and downstream flows of products, services, finances,
and/or information from a source to a customer.” (Mentzer et al. 2001) Depending on the degree of
complexity of the SC, and the number of actors, the SC may present different levels of analysis. In this
paper, we concentrate on SCs involving manufacturer, retailers, and logistics providers.
Within the SC, close cooperation enables the overall SC profitability (Simatupang and Sridharan 2002).
Furthermore, information sharing is key since inefficiencies are mainly linked to asymmetric information
or distorted information (Lee et al. 1997; Wang and Wei 2007). Information can be viewed as a tool
permitting to coordinate interorganizational activities, as well as a means for reducing cost and improving
the overall SC efficiency (Tan 2001). Questions are therefore on how individual organization accepts to
share information and on the type of information shared. A firms’ willingness to share information
appears to be dependent upon the type of information. Frazier et al. (Frazier et al. 2009) suggest that
strategic information sharing should be considered from two different levels: internal strategic
information (internally processed data on future long-term plans) and external strategic information
(externally processed data on customers and competitors). Internal strategic information is proprietary
sigIQ pre-ICIS workshop 2011 2
IQ for the Transformation into Green SC
and sensitive information whilst external strategic information is nonproprietary and thus less sensitive
since it originates from outside of the firm.
Understanding how information is shared leads researchers to take into account considerations about
coordinating activities and decision making along the SC (Frazier et al. 2009). Ideally, as these authors
further explain, the decision-making is under the control of one single actor, such a system is referred to
as a centralized system. In a decentralized system, entities of a SC pursue their own goals and optimize
their own benefits. In such systems, there is a need for some incentive and action plans in order to
allocate resources efficiently and distribute benefits among the participating units.
In order to meet stakeholders’ pressure (Hall 2001) as well as growing environmental regulations (Delmas
and Montes-Sancho 2011), SCs are evolving to include consideration of environmental externalities
(greenhouse gas, pollution, and waste). Environmental goals and industrial competitiveness have for
quite some time been considered as antinomies and therefore the GSC was only for companies that could
afford it (Corbett and Klassen 2006). In particular, several firms claiming to be “environmental
compliant”, “socially responsible”, and pursuing “sustainable growth strategies” have still not
implemented an Environmental Management System (EMS) nor adopted the international environmental
standard of ISO14001. If 83% of the companies declare to take into account environmental concerns in
their strategic decisions, only 35% of them confirm that they are currently operating in, or part of, a GSC
(Carbone and Moatti 2008).
Combining economical and environmental performance of SCs seems to be a real challenge for the 21st
Century. On the one hand, some authors do claim that environmental improvements do not necessary
imply heavy investments. Being green improves productivity and that’s where one may argue that GSCM
is a true competitive advantage (Porter and van der Linde 1995). Pollution control preventions are costeffective actions, not only for the environment but also from the economic point of view of the firm. On
the other hand, some researchers find an exponential growth of total logistics costs across the SC when
reducing the level of CO2 (Wang et al. 2011). For instance, a 17% reduction in greenhouse gasses requires
a logistic cost increase of 10,097% (Chaabane et al. 2008).
Information Quality as an Enabler of GSCM
For close cooperation and development of new SC forms and objectives, both data consistency and crossfunctional SCM application integration are important elements for IT infrastructure integration (Rai et al.
2006). In particular, “data consistency is relatively more important, in comparison to cross-functional
application integration, suggesting the high degree of importance of data quality and standards as
facilitators of process integration”. Moreover, in SC networks IQ is a predictor and enabler of firm
performance (Ramayah and Omar 2010). However, the SCM literature has not paid enough attention to
IQ. The question of the contribution of IQ to the development of GSCM has to be investigated. In
particular, IQ is a multi dimensional concept (Ballou and Pazer 1985; Sarkis et al. 2011; Wang and Strong
1996) as shown on table 1. In SCM literature, IQ dimensions that are valuable and/or necessary for
supporting current SC evolution are not well understood. Pierce (2005) built a fictional case on the order
process of an online retailer and proposes a Quality Specification table for a customer order based upon
Wang and Strong (1996). This proposal is interesting but not sufficient. First of all, it is based upon a
fictional case and not real-life empirical data. Second, it does not identify the specific quality dimensions
that will have significant economic and environmental consequences. The analysis of which IQ
dimensions have to be taken into account and managed for environmental benefits development, is
therefore both theoretically and empirically important. Among the different research that propose several
dimensions for IQ, this paper relies on the Wang and Strong (1996) classification (Table 1). Indeed, recent
research (Madnick et al., 2009; Sadiq et al. 2011) explained that this classification can be viewed as a basis
for IQ research.
Table 1: Data Quality dimensions (Wang and Strong 1996)
DIMENSION
DEFINITION
Accuracy
The extent to which data are correct, reliable, and certified free of error
Believability
The extent to which data are accepted or regarded as true, real, and credible
sigIQ pre-ICIS workshop 2011 3
IQ for the Transformation into Green SC
Objectivity
The extent to which data are unbiased (unprejudiced) and impartial
Reputation
The extent to which data are trusted or highly regarded in terms of their source
or content
Value-Added
The extent to which data are beneficial and provide advantages from their use
Relevancy
The extent to which data are applicable and helpful for the task at hand
Timeliness
The extent to which the age of the data is appropriate for the task at hand
Completeness
The extent to which data are in sufficient breadth, depth, and scope for the task
at hand
Appropriate
amount of data
The extent to which the quantity or volume of available data is appropriate
Interpretabilty
The extent to which data are in appropriate language and units and the data
definitions are clear
Ease
of
understanding
The extent to which data are clear without ambiguity and easily comprehended
Representatio
nal consistency
The extent to which data are always presented in the same format and are
compatible with previous data
Concise
representation
The extent to which data are compactly represented without being overwhelming
Accessibility
The extent to which data are available or easily and quickly retrievable
Access security
The extent to which access to data can be restricted and hence kept secure
Methodology
The empirical approach relies on qualitative methods, because the research is mainly exploratory
(Georges and Bennett 2005). Moreover, identifying the type of information and IQ dimensions that are
relevant for GSCM development involves a deep understanding of processes and context of a SC. We
therefore conducted a case study in the retail industry and performed eight interviews in 2011,
constituting the primary source of data. The interviews have been tape-recorded and transcribed to
ensure the validity of the findings. They are detailed in table 2 presenting the type of firms (retailer,
manufacturer, logistic service provider) and interviewees’ positions. We had access to documents, public
and private presentations as well as use of the information system at the manufacturer site and
consolidation center (CC), a type of large warehouse, each visited for one day.
The interview script was adapted for interviewees’ company and position, even though it was structured
around four main areas. The first part concerns the description of current sharing operations developed to
transform SCs the firm is operating in. This allows us to identify SC processes the firms consider as key to
develop GSCM. The second section examines the characteristics of the IS including relevant information.
The third part focuses on IQ. This part asked questions about dysfunctions in the current experiences.
This allows identifying which failures or problems are derived from poor IQ. The fourth part concerns the
effects of shared experiences, both from economic and environmental considerations.
Table 2. List of interviewees
Firm Type
Interviewee Position
Retailer
France SC Director
Retailer
External Relations France SC Director
Retailer
CC Project Leader
Retailer
CC Operations Manager
sigIQ pre-ICIS workshop 2011 4
IQ for the Transformation into Green SC
Manufacturer Food 1
SC Manager #1 (2 interviews)
Manufacturer Food 2
SC Manager #2
Third Party Logistics Service Provider
CC Director (3PL)
Information Systems Provider
Key Account Manager
We conducted a thematic qualitative analysis of the interview transcripts (Miles and Huberman 1994).
Analysis of the interviews was conducted from a dictionary of evolutionary themes, derived from both the
literature review and field study considerations that have emerged. The dictionary themes are related to
four major categories (process, type of information, IQ dimensions, and effects). By using the 15
dimensions of Wang and Strong (1996) for coding interviews, we were able to quantifiably identify in each
interview the IQ dimensions that are more relevant to support SC transformation.
For the purpose of this study we focused on non-perishable goods. We realized in the interview process
that there is a distinction with perishable and non-perishable goods. With perishable goods a new
dimension including the use of cold storage facilities, refrigerated trucks, and shorter timetables were a
factor. For this study we focused on the supply chain that did not concern these aspects of perishable
goods.
Results
The Transformation of the Supply Chain
The retailer interviewed was a major French company ABC (pseudonym), with domestic and international
operations. We focused our SCM to a portion of the French operations. ABC’s first objective was to
increase the rate of fulfillment of trucks while increasing the delivery rate to its stores. “In the AngloSaxon world delivery at the point of sale occurs 3 to 4 times a day, while our manufacturers sometimes
only deliver once or twice a week” (France SC Director). The second objective is to control logistical costs
so that transportation cost and warehousing cost be limited to the initial cost before the transformation.
“We are a sales firm and we almost have one m2 for the sales to one m2 for the stock. Is that a normal
ratio? At a point of sale, we have 10-12 days of stock whereas we receive goods daily. There is something
wrong in our model” (id.). However ABC seeks more gains on the real estate necessary to maintain the
stock than on the assets represented by the stock level itself. “Most important is not the reduction of the
stock but diminishing the ground space we use”. Finally the third objective is to reduce CO2 emissions.
“One of our main preoccupations to reduce the costs is the level of stock we have on the whole supply
chain…this means we respond to the need of the outlet which is to be served daily in small amounts. We
do not destroy the environment because, on the whole chain, the truck is full” (France SC Director).
To meet these three objectives, ABC transformed its SC as follows. ABC first launched a pilot with three of
its regional warehouses, two small and medium enterprises (SME) and a third party logistics in 2004.
Results over the year 2006 were positive and the three objectives were met. 121 tons of CO2 emissions
were saved and the model was then spread to all warehouses with 12 manufacturers. A first CC was
implemented in 2007, but was stopped due to the inadequate IS supporting the CC. The real
industrialization and deployment of the new design of the whole SC began in 2009. ABC’s ambition is to
integrate all its small manufacturers into this resource-sharing scheme, which requires a large scale
implementation. A survey performed by ECR France shows that half of deliveries are done with fewer
than 5 pallets. Thus logistics and transportation are far from being optimized. The new, shared design was
to drastically improve the situation. First for manufacturers, the points of delivery are reduced from 21
warehouses to 2 CCs, one each respectively for the southern and the northern warehouses (cf. Figures 1
and 2). Currently 400 manufacturers have adopted this scheme, while the remaining 1100 continue with
the former scheme. The CC does not belong to ABC, rather a third party logistics operator (3PL) owns and
operates the CC and signs contracts with the manufacturers. ABC negotiates with the 3PL and says to the
small manufacturer “We assure you that costs are right, hence you can trust us. However the contract is
with the 3PL. We negotiate the basic service and the manufacturer can benefit from an à la carte
treatment. We don’t intervene after that” (France SC Director). “The stock on the CC still belongs to the
sigIQ pre-ICIS workshop 2011 5
IQ for the Transformation into Green SC
manufacturer…The manufacturer can serve the needs of all its clients. Sharing at the CC is not exclusively
for ABC” (External Relations France SC Director).
50
%
ABC
100 %
ABC
ABC
ABC
1500 SMEs
ABC
ABC
1500 Points of Sales (PoS)
21 Regional Warehouses
Figure 1. Pysical Flows Manufacturer-Retailer before CC implementation
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
400 SMEs
2 CC
(North/South)
21 Regional Warehouses
1500 PoS
Figure 2. Physical Flows Manufacturer-Retailer after CC implementation
sigIQ pre-ICIS workshop 2011 6
IQ for the Transformation into Green SC
IS Architecture Evolution
In order to manage information exchange with the manufacturer and the diverse 3PL operating the CC,
the retailer has implemented a Web portal created by Generix: “we are operating with SMEs and they do
not have competencies and financial capabilities for a complex system appropriation. There are additional
costs that may be prohibitive for them. Hence the idea they share costs by the use of a Web portal shared
with the 3PL” (CC project leader). Purchase orders are sent to the manufacturer and copied to the 3PL, so
that the 3PL can plan the organization of delivery.
Manufacturers can use “full-EDI” (Electronic Data Interchange), and therefore validate automatically
orders for the 3PL to prepare products stocked in the CC for delivery. When manufacturers are not “fullEDI”, but just “Web-EDI”, they have to connect themselves to the Web portal and validate each purchase
order: “To facilitate manufacturer’s work, avoid errors, and save time, orders are available in the tool, so
that the manufacturer just has to validate them. The manufacturer can validate or not, but they do not
need to reenter data” (CC Project Leader). With Web-EDI, beyond a certain volume amount and
frequency of delivery, there were issues of IQ and staff that made it advantageous even for SMEs to go
with full-EDI. “With the ABC’s request to go with daily deliveries, we would have needed to hire a person
at half-time just to key-in the data to the web-EDI system, but this caused errors. Hence our solution was
to go to full-EDI and get rid of manual data handling and possible errors” (SC Manager #1). Another
important point is that the manufacturer can access through the web portal to check its stock levels but
not stock movements: “It would be a good idea if the 3PL could indicate stock movements in the CC, this
would allow automating delivery orders between suppliers and CC, taking care of decisions and
constraints they define” (CC Project Leader). Figure 3 synthesizes information exchanges between SMEs,
CC, and the retailer through the Web portal.
1- Orders from
all point of sales
Manufacturer
(SME)
2- Orders
validation
Retailer
Central IS
Web portal
3- Expedition
confirmation
4- Stock levels
evolution and
delivery order if
necessary
CC (3PL)
Figure 3. Information Exchange within the Supply Chain (Orders are a solid line, order validation is a dotted
line, information flow from the manufacturer is a dashed line, and the information flow from the CC to the
retailer central server is a dashed and dotted line)
sigIQ pre-ICIS workshop 2011 7
IQ for the Transformation into Green SC
IQ as an Enabler of GSCM
From the interviews, we can infer that both orders and stock levels have to be managed differently with
the evolution of the physical and informational flows. The question of quality of these pieces of
information is important for the performance of SC evolution.
Concerning stock levels, the SC Director of the retailer explains that it would be valuable to transfer
information about the actual sales of the products by store to the manufacturer in a timely manner: “we
are thinking about the way we could share information in order to make them accessible to the small
manufacturers… But when you give all ticket sales from several thousands of point-of-sale locations to a
manufacturer, it’s such a huge amount of information”. The SMEs do not have sufficient IS capabilities to
integrate and manage the quantity of information about real-time sales to develop the overall SC
performance. Indeed, for the moment, enhancing the amount of information exchanged would definitely
introduce an overwhelming effect for the supplier. For SMEs, concise representation of the relevant
information is not compatible with the development of the amount of data exchanged with the retailer.
Therefore, stock levels have to be managed in the CC by the 3PL and be accessible to the manufacturer in
real-time through the IS platform. The manufacturer can therefore anticipate and manage the supplying
of the CC with full trucks: when accuracy, timeliness, and accessibility of stock levels in the CC are good
enough, the manufacturer operates in a less uncertain environment. Therefore it “can optimize CC
delivery” and move towards GSCM with full trucks from the manufacturer’s warehouse to the CC.
When IQ is not sufficient, orders can be blocked and the delivery of the product from the CC to retailer
warehouses is not optimized. Indeed, if a manufacturer and the 3PL cannot coordinate the order,
shipment will not be optimized: “trucks will not be full, because a product we planned to load in the truck
is not added” (3PL). So environmental benefits of SC transformation are not efficient.
“Orders are recognized by the association of an EAN-13 code (European Article Number), GLN code
(Global Location Number). identifying the supplier and the products per order (PPO: number of products
included in the ordering element [products/pallet])” (3PL). When one of these elements suffers from poor
quality, the SC is immediately threatened. In particular, accuracy of these pieces of information is crucial.
As the CC operations manager explains: “Look, this order has been rejected because there is something
wrong. There is a difference between the PPO we have created ourselves and the PPO transmitted by the
retailer”. Information accuracy in purchase orders is therefore crucial for the SC performance. Similarly,
completeness is necessary, since missing information does not allow realization of the transaction. In
addition, the extent to which data are always presented in the same format is a real advantage of the SC
evolution. Because the manufacturer, supplier, and 3PL share a common platform to exchange
information, they share the representational consistency of purchase orders and ease of understanding is
improved: “It took a long time, but now, with the standardization, we understand orders faster from [the
retailer]” (SC Manager #2).
Finally, the purchase order must not only be clean but it also needs to be transmitted in a timely manner
and accessible to the manufacturer. With the development of just-in-time delivery by the retailer,
information has to be exchanged without delay for the shipment to be realized on time. However, since
the manufacturer has to connect to the platform to validate orders for those using the web based EDI,
information must also be accessible in a timely manner. So that “I advise the supplier to connect twice. At
8am since orders arrive at 8, and at 10am to verify if and whether the order did not pass” (3PL).
Discussion and Conclusion
The strengths of this study are three-fold. First, we have shown the role IQ can play in SC architecture and
IS transformation for the development of the GSC, especially via greenhouse gas reduction from
transportation optimization. Table 3 summarizes the results by presenting the dimensions of IQ that may
enable firms to perform GSCM in SC transformation.
Table 3. Information Quality dimensions to support supply chain
transformation
Information
Quality
Information
examples
Dysfunctions/ Problems
Environmental impacts
sigIQ pre-ICIS workshop 2011 8
IQ for the Transformation into Green SC
dimensions
Accuracy
Timeliness
Completeness
Information
included
in
purchase orders
and stock levels
Unknown
product
identification => purchase
order blocked and delivery
delayed or delivery of wrong
product
Wrong order quantity or place
=> additional transportation
Purchase orders
exchange
and
purchase orders
validation
Purchase order transmitted or
validated too late => lead time
conflict and impossible to
respect delivery date and time
Information
included
in
purchase orders
and stock levels
Missing
information
in
purchase order => purchase
order blocked
Missing inventory information
=> wrong supply calculation
Waste of material, energy, fuel,
transportation and increased
CO2
Additional
difficulties
to
anticipate
planning
of
transportation or warehousing
activities
Additional CO2 and nonoptimized transport (partial
delivery).
Waste of material, energy, fuel,
transportation, and increased
CO2
Additional CO2 and nonoptimized transport (partial
delivery).
Appropriate
amount of data
Stock levels
Suppliers do not have the
capabilities to manage sales
information
Ease
of
understanding
Purchase orders
Information is not presented
in the same format between
various actors of the SC
Purchase orders
Information is not presented
in the same format between
various actors of the SC
Concise
representation
Stock levels
Suppliers do not have the
capabilities to manage sales
information
Additional
difficulties
to
anticipate
planning
of
transportation or warehousing
activities
Accessibility
Purchase orders
and Stock levels
Information is not accessible
Additional CO2 and nonoptimized transport (partial
delivery).
Representational
consistency
Additional CO2 and nonoptimized transport (partial
delivery).
Consequently, practitioners such as SC managers may concentrate on these IQ dimensions to develop
GSCM in order to meet both stakeholder pressure (Hall 2001) and growing environmental regulations
(Delmas and Montes-Sancho 2011). Second, we were given access to three players (manufacturer, retailer,
and logistics operator) in the SC. We were able to use real data from a leader in the retail business in
France. Third, we see there is a lack of studies that look at the SC from an IQ point of view. We feel that
this study is one of a few studies that have used IQ to identify difficulties in the transformation of a SCM
into a GSCM.
The limitations of this study are two-fold. First, we used only eight interviews, while covering all players in
the SC, a larger interview pool, may or may not reveal hidden details about the SC. Second, this was only
one player in the retail business in the French market and two manufacturers, which may or may not
apply to the organizing of other SCM.
Some areas of future research can also be identified from this analysis. First, an interesting area to
investigate is if the results may be generalized to other types of products or services in different SC
configurations. Complementary analysis may be achieved to understand how companies manage IQ
sigIQ pre-ICIS workshop 2011 9
IQ for the Transformation into Green SC
internally before and after exchanges in order to identify best practices. Contrary to some research
explaining that reducing CO2 emissions induces additional logistics costs across the SC (Chaabane et al.
2008; Wang et al. 2011), our results are more in line with Porter and van der Linde (1995): green
considerations are correlated to productivity improvement since being green can only occur when
economic benefits are first assumed. Indeed, information sharing and IQ are a prerequisite to SC
operations optimization and SC operations optimization means both economic and environmental
benefits for the whole SC. In addition, in order to achieve current environmental concerns (Sarkis et al.
2011; Wang et al. 2011), one must address the issue of repartition of economic benefits among the
different actors of the SC. Moreover, the correlation between economic and environmental benefits needs
to be better understood. From the field study conducted, we can conclude that IQ improvement
considerations for the development of the GSC are first derived from efficiency improvement.
References
Ballou, D., and Pazer, H. 1985. "Modeling Data and Process Quality in Multi-Input, Multi-Output
Information Systems," Management Science (31:2), pp. 150-162.
Bowersox, D., Closs, D., and Drayer, R. 2005. "The Digital Transformation: Technology and Beyond,"
Supply Chain Management Review), January, 2005, pp. 1-9.
Carbone, V., and Moatti, V. 2008. "Greening the Supply Chain: Preliminary Results of a Global Survey,"
Supply Chain Forum: An International Journal (9:2), pp. 66-76.
Chaabane, A., Ramudhin, A., Paquet, M., and Benkaddour, M.A. 2008. "An Integrated Logistics Model for
Environmental Conscious Supply Chain Network Design," in: Americas Conference on Information
Systems. Toronto, ON Canada.
Corbett, C.J., and Klassen, R.D. 2006. "Extending the Horizons: Environmental Excellence as Key to
Improving Operations," Manufacturing & Service Operations Management (8:1), pp. 5-22.
Delmas, M., and Montes-Sancho, M. 2011. "An Institutional Perspective on the Diffusion of International
Management System Standards: The Case of the Environmental Management Standard Iso 14001,"
Business Ethics Quarterly (21:1), pp. 103-132.
Forrester, J.W. 1958. "Industrial Dynamics: A Major Breakthrough for Decision Makers,," Harvard
Business Review), July-August 1958, pp. 37-66.
Frazier, G., Maltz, E., Antia, K., and Rindfleisch, A. 2009. "Distributor Sharing of Strategic Information
with Suppliers," Journal of Marketing), July 2009, pp. 31-43.
Georges, A., and Bennett, A. 2005. Case Studies and Theory Development in the Social Sciences, Belfer
Center for Science and International Affairs,. Harvard University.
Hall, J. 2001. "Environmental Supply Chain Innovation," Greener Management International (35), pp.
105-119.
Hartono, E., Li, X., Na, K.S., and Simpson, J.T. 2010. "The Role of the Quality of Shared Information in
Interorganizational Systems Use," International Journal of Information Management (30:5), pp. 399407.
Lambert, D., and Cooper, M. 2000. "Issues in Supply Chain Management," Industrial Marketing
Management (29:1), pp. 65-83.
Lee, H.L., Padmanabhan, V., and Whang, S. 1997. "Information Distorsion in a Supply Chain: The
Bullwhip Effect," Management Science (43:4), pp. 546-558.
Legner, C., and Schemm, J. 2008. "Toward the Inter-Organizational Product Information Supply Chain –
Evidence from the Retail and Consumer Goods Industries," Journal of the Association for
Information Systems (9:4).
Madnick, S., Wang, R., Lee, Y., and Zhu, H. 2009. "Overview and Framework for Data and Information
Quality Research," ACM Journal of Data and Information Quality (1:1).
Melville, N.P. 2010. "Information Systems Innovation for Environmental Sustainability," MIS Quarterly
(34:1), March 2010, pp. 1-21.
Mentzer, J.T., DeWitt, W., Keebler, J.S., Min, S., Nix, N.W., Smith, C.D., and Zacharia, Z.G. 2001.
"Defining Supply Chain Management," Journal of Business Logistics (22:2), pp. 1-25.
Miles, M.B., and Huberman, A.M. 1994. Qualitative Data Analysis. Thousand Oaks: Sage Publications.
Pierce, E. 2005. "What's in Your Information Product Inventory?," in Information Quality, R. Wang, E.
Pierce, S. Madnick and C. Fisher (eds.). Armonk, NY: M.E. Sharpe, pp. pp. 99-114.
sigIQ pre-ICIS workshop 2011 10
IQ for the Transformation into Green SC
Porter, M.E., and van der Linde, C. 1995. "Toward a New Conception of the Environment-Copetitiveness
Relationship," Journal of Economic Perspectives (9:4), Fall 1995, pp. 97-118.
Rai, A., Patnayakuni, R., and Seth, N. 2006. "Firm Performance Impacts of Digitally Enabled Supply
Chain Integration Capabilities.," MIS Quarterly (30:2), pp. 225-246.
Ramayah, T., and Omar, R. 2010. "Information Exchange and Supply Chain Performance," International
Journal of Information Technology & Decision Making (9:1), pp. 35-52.
Sadiq, S., Yeganeh, N., and Indulska, M. 2011. "20 Years of Data Quality Research: Themes, Trends and
Synergies. ," in: The 22nd Australasian Database Conference. Sidney, Australia.
Sarkis, J., Zhu, Q., and Lai, K.-h. 2011. "An Organizational Theoretic Review of Green Supply Chain
Management Literature," International Journal of Production Economics (130:1), pp. 1-15.
Simatupang, T., and Sridharan, R. 2002. "The Collaborative Supply Chain: A Scheme for Information
Sharing and Incentive Alignment," International Journal of Logistics Management (13:1), pp. 15-30.
Tan, K.C. 2001. "A Framework of Supply Chain Management Literature," European Journal of Purchasing
& Supply Management (7:1), pp. 39-48.
Wang, E., and Wei, H. 2007. "Interorganizational Governance Value Creation: Coordinating for
Information Visibity and Flexibility in Supply Chains," Decision Science (38:4), pp. pp. 647-674.
Wang, F., Lai, X., and Shi, N. 2011. "A Multi-Objective Optimization for Green Supply Chain Network
Design," Decision Support Systems (51:2), pp. 262-269.
Wang, R., and Strong, D. 1996. "Beyond Accuracy: What Data Quality Means to Data Consumers,"
Journal of Management Information Systems (12:4), pp. pp. 5-34.
Wiengarten, F., and Humphreys, P. 2010. "Collaborative Supply Chain Practices and Performance:
Exploring the Key Role of Information Quality," Supply Chain Management: An International Journal
(15:6), pp. pp. 463-473.
sigIQ pre-ICIS workshop 2011 11