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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