614 Understanding the Development of Free E-Commerce/E-Business Software FOSSD Capability Enabling Free, Open ERP, and EC/EB Systems The array of social, technological, and informa- tional resources that enable a FOSS development project like GNUe is substantial. However, they differ in kind and form from the traditional enter- prise resources that are provided to support pro- prietary, closed source software systems. These traditional software engineering resources are money (budget), time (schedule), skilled (salaried) development staff, project managers (adminis- trative authority), quality assurance (QA) and testing groups, documentation writers, computer hardware and network maintainers, and others (cf. Sommerville, 2004). Free software projects like GNUe seem to get by with comparatively small amounts of money, though subsidies of various kinds and sources are present and necessary. They also get by without explicit schedules, though larger projects may announce target release dates, as well as (partially) order which system functions or features will be included in some upcoming versions, for some target releases. Further, they get by without a rule-making and decision-making authority of corporate project managers or enter- prise executives, who may or may not be adept at empowering, coaching, or rewarding development staff to achieve corporate software development goals. Instead, in GNUe, participants rely on an implicit but frequently recited regime of beliefs, values, and norms that help organize coopera- WLYHDFWLYLW\ DQG UDWLRQDOL]H FRQÀLFWPLWLJDWLRQ (Elliott & Scacchi, 2003, 2005). The remaining resources are provided within a free software development effort via subsidies, sponsorship, or volunteer effort. Thus, the resources for free software develop- ment efforts are different in kind, and in how they are arrayed and brought to bear when compared to a traditional software engineering effort. Free software project resources are not mobilized, al- located, or otherwise brought to bear in the man- ner traditional to the development of proprietary, closed source software systems. Hopefully, it should be clear that the differences being high- lighted are not based simply on a comparison of functionality or features visible in the develop- ment or use of open vs. close source software products. As such, the resource-based capability for developing free software packages for ERP and EC/EB applications is different, though not necessarily more or less costly. DISCUSSION AND CONCLUSION Many questions about free software development remain u nanswered or unexamined by this st udy. For example, it is unclear whether there must be a critical mass of salaried software developers whose job includes development or support of GNUe software, and if so, how many software developers this entails. Over the four years in the study of GNUe, the number and composition of core software developers has changed, partly in response to their changing interests and work situations. The project has not grown to the point where commercialization of the GNUe software has become an imperative or new venture start- up opportunity, as has happened with OSS ERP projects of Compiere, OpenMFG, and Openbravo. Thus, it is unclear whether GNUe will become a viable enterprise capable of hiring a professional or full-time staff, as well as engaging in con- tracted provision of installation, customization, and support services that normally accompany ERP and EC/EB software packages. Further comparative study of other free software projects and their approach for commercialization are needed. However, it does seem clear that GNUe has managed to sustain itself as a viable ongoing enterprise that continues to develop and sustain free ERP and EC/EB software packages, which its developers use and deploy in their day jobs or consulting practices. 615 Understanding the Development of Free E-Commerce/E-Business Software Beyond this, three conclusions can be drawn from the study, data, and analysis presented in this UHSRUW)LUVWWKLVFKDSWHULGHQWL¿HVPDQ\W\SHV of socio-technical resources and resource-based capabilities for free EC/EB that may explain/pre- dict (a) what’s involved, (b) how it works, or (c) what conditions may shape the longer-term suc- cess or failure of such efforts. In simple terms, these resources include time, skill, effort, belief, personal and corporate subsidies, and commu- nity building on the part of those contributing as developers and users of free EC/EB systems and techniques. Of these, belief in the freedoms that open source system development embraces, including freedom of choice and freedom of ex- pression (Elliott & Scacchi, 2003, 2005, 2006) appears central. Such belief in turn enables and af- fords the ongoing commitment, development, and articulation of a web of social, technological, and information resources that sustain a free software project, without the traditional administrative and ¿QDQFLDOUHVRXUFHVIRXQGLQWUDGLWLRQDOVRIWZDUH development enterprises. Developers and users who believe in the promise and potential of free ERP or EC/EB packages are willing to allocate (or volunteer) their time and apply their skills to make the effort of developing or using open source systems a viable and successful course of action. Thus, companies seeking to invest in or exploit free EC/EB techniques or systems must account for how it can most effectively cultivate a free software culture, belief system, and community of practice, as part of their strategic choice. 6HFRQG WKLV LV WKH ¿UVW VWXG\ WR HPSOR\ D resource-based view of a FOSS development project. The resource-based view of organiza- tional capability and competitive advantage is the dominant analytical lens employed in studies of organizational strategy and strategic management (cf. Acedo et al.,2006; Barney, 2001). Why should people interested in FOSS development practices be concerned or interested in such a strategic per- spective? Many reasons might be cited in support, but attention here can be drawn to determining whether free software systems and development methods offer sustained or differentiated ad- vantages over traditional software engineering approaches applied to the development of close source, proprietary (non-free) software systems. If there are advantages that can be traced to the resource arrangements found in free software proj- ects like GNUe, then these would be noteworthy ¿QGLQJVDVZHOODVDSRVVLEOHEDVLVIRUIXUWKHU exploration and theorizing. Accordingly, in the GNUe case, resources like personal computing tools that help subsidize the development effort, beliefs that provide a cultural basis for making decisions about technical choices, trust and social accountability, discretionary software develop- ment work times, and the preferred use of software informalisms instead of software engineering IRUPDOLVPV OLNH ³UHTXLUHPHQWV VSHFL¿FDWLRQV´ DQG³SURMHFWPDQDJHPHQWSODQV´DOOGLIIHUHQWLDWH the practice of free software development from that advocated in traditional software engineering textbooks (e.g., Sommerville, 2004). Last, this study links free software with ERP and EC/EB. No prior case studies of ERP or EC/ (%V\VWHPVKDYHLGHQWL¿HGRUDGGUHVVHGZKHWKHU or how free software (or open source software) methods might be used to develop or integrate EC/ EB software packages, at least beyond the use of OSS Web servers or Web site content management systems (Carbone & Stoddard, 2001). Thus, there LVDQRSSRUWXQLW\IRU¿UPVWREHJLQFRQVLGHULQJ whether these results merit timely consideration or exploratory investments in free software or OSS. For example, companies offering consumer products or high value, information technology- based products and services may begin to consider whether free EC/EB capabilities that offer lower purchase prices, lower total cost of ownership, and higher quality (Scacchi, 2002b) represent new market entry or new product differentiation RSSRUWXQLWLHV6LPLODUO\FRPSDQLHVPD\¿QG that free/open source software represents a new, 616 Understanding the Development of Free E-Commerce/E-Business Software highly innovative approach to software product or application system development that marries the best capabilities from both private investment and collective action (von Hippel & von Grogh, 2003; Olson, 1971). REFERENCES Acedo, F. J., Barroso, C., & Galan, J. L. (2006). The resource-based theory: Dissemination and main trends. Strategic Management J., 27(7), 621-636. Ackerman, M., & Halverson, C. (2000, January). Reexamining organizational memory, Commu- nications ACM, 43(1), 59-64. Barney, J. B. 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Sebastopol, California: O’Reilly Books. ENDNOTES 1 The research described in this report was supported by grants from the U.S. National Science Foundation Industry/University Research Cooperative CRITO Consor- tium; the National Science Foundation #0083075, #0205679, #0205724, #0350754, and # 0534771; and the Defense Acquisition University by contract N487650-27803. No endorsement implied. 619 Understanding the Development of Free E-Commerce/E-Business Software 2 Compiere.com is a software product devel- opment community that is building an open source software ERP system that requires the use of Oracle. It is not, however, free soft- ZDUHDVLQ³IUHHGRP´VRIWZDUH:LOOLDPV 2002). Compiere.com, however, claims more than 500K copies of its software have been downloaded or installed, making it the most widely deployed ERP system in the world, whether as a proprietary or FOSS-based offering. 3 End-user license agreements (EULAs), as- sociated with probably all software, often VHHNWRGHFODUH³IUHHGRPIURPOLDELOLW\´IURP people who want to use licensed software for intended or unintended purposes. But liability freedom is not the focus here. This work was previously published in Electronic Commerce: Concepts, Methodologies, Tools, and Applications, edited by A. Becker, copyright 2008 by Information Science Reference (an imprint of IGI Global). 620 Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 2.18 Balancing Accuracy of Promised Ship Date and IT Costs Young M. Lee IBM T. J. Watson Research Center, USA ABSTRACT In an ideal e-business environment, when a customer order is scheduled and a ship date is computed, the availability should immediately be reserved and not be available for future orders. However, in reality the availability data that are used for the scheduling the orders are not real time availability (physical availability), but they are availability information stored in an IT system (system availability). The availability data in the IT system (static view of availability) is typically refreshed (synchronized with real time availabil- ity) only periodically since it is very expensive to update the database in real time. Due to this potentially inaccurate view of the availability, some orders cannot be shipped on the promised ship date. Therefore, for certain customer orders, products are shipped later than the promised ship date resulting in customer dissatisfaction. There- IRUH RQH RI NH\ GHFLVLRQV LQ RUGHU IXO¿OOPHQW process is to properly balance IT system (e.g., IT expense) and accuracy of promised ship date. In this work, we study how availability fresh rate (IT system) impacts customer service level. The simulation model we develop helps making critical business decision on refresh rate of availability, and avoiding expensive IT investment. INTRODUCTION Being able to promise customers the desirable GHOLYHU\GDWHDQGIXO¿OOLQJWKHRUGHUVDVSURPLVHG are an important aspects of customer services. With the recent surge and widespread use of e- commerce, shoppers can now easily assess and compare customer service quality in addition to quality of goods and price among different vendors. This creates a very competitive business environment, thus making customer service a critical factor for success and survival of many companies. Competitive pressures are forcing companies to constantly look for ways to improve customer services by evaluating and redesigning supply chain processes. Availability Management Process (AMP), also called Available-to-Promise (ATP) process, is a key supply chain process that 621 Balancing Accuracy of Promised Ship Date and IT Costs impacts customer service since it determines customer promised ship (or delivery) dates, the accuracy of the promised ship date, order sched- XOLQJGHOD\DQGRUGHUIXO¿OOPHQWUDWHDVZHOODV inventory level. The availability management involves generat- ing availability outlook, scheduling customer or- GHUVDJDLQVWWKHDYDLODELOLW\RXWORRNDQGIXO¿OOLQJ the orders. Generation of Availability Outlook is a push-side of the availability management process, and it allocates availability into ATP (Available- to-Promise) quantities based on various product and demand characteristics and planning time periods. Order Scheduling is a pull-side of avail- ability management process, and it matches the customer orders against the Availability Outlook, determines when customer order can be shipped, and communicates the promised ship date to FXVWRPHUV 2UGHU IXO¿OOPHQW LV H[HFXWLQJ WKH shipment of the order at the time of promised ship date. Even if an order is scheduled for shipment for a certain date based on the outlook of avail- ability, the resources that are required to ship the product on the promised ship date may not actu- ally available when the ship date comes. A key role for effective availability management process is to coordinate and balance the push-side and pull-side of ATP, and to have adequate Informa- tion System (IS) capability so that desirable and accurate ship date is promised to customer and product is shipped on the promised date. AMP or ATP process has been described in several research papers. Ball, Chen, and Zhao (2004) gave an overview of the push-side (Avail- ability Planning) and pull-side (Availability Promising) of ATP with examples from Toshiba, Dell, and Maxtor Corporation. They stressed the importance of coordinating the push and pull- side of availability management for supply chain performance by making good use of available resources. Although ATP functions has been available in several commercial ERP and Supply Chain software such as SAP’s APO, i2’s Rhythm, Oracle’s ATP Server and Manugistics’ SCPO modules, and so forth for several years (see Ball et al. (2004) for details), those ATP tools are mostly fast search engines for availability database, and they schedule customer orders without any so- phisticated quantitative methods. Research on the quantitative side of ATP is still at an early stage, and there are only a limited number of analytic models developed in supporting ATP. For the push-side of ATP, Ervolina and Dietrich (2000) developed an optimization model as the resource allocation tool, and described how the PRGHOLVXVHGIRUDFRPSOH[&RQ¿JXUHGWR2UGHU (CTO) environment of the IBM Server business. They also stress how the push-side (Availability Promising) and pull-side (Availability Planning) have to be work together for the overall availability management performance. For the pull-side of ATP, Chen, Zhao, and Ball (2002) developed a Mixed-Integer Program- ming (MIP) optimization model for a process where order promising and fulfillment are KDQGOHGLQDSUHGH¿QHGEDWFKLQJLQWHUYDO7KHLU model determines the committed order quantity for customer orders that arrive with requested delivery dates by simultaneously considering material availability, production capacity as well as material compatibility constraints. They also studied how the batching interval affects sup- ply chain performance with different degree of resource availability. Moses, Grand, Gruenwald, and Pulat (2004) also developed a model that computes optimal promised ship date considering QRWRQO\DYDLODELOLW\EXWDOVRRWKHURUGHUVSHFL¿F characteristics and existing commitments to the previous scheduled orders. Pan and Shi (2004) also developed a heuristics-based order promis- ing model but with E-commerce environment in mind. They modeled a process where customer orders arrive via Internet and as earliest possible shipment dates are computed in real-time and is promised to customers. All the previous work described above deal with either push-side of ATP or pull-side of ATP with an assumption that accurate inventory data 622 Balancing Accuracy of Promised Ship Date and IT Costs are available in real time. However, in reality the inventory data is less than perfect, and even if the optimal ATP tools were in place, order IXO¿OOPHQWSHUIRUPDQFHZRXOGEHOHVVWKDQRS- timal. The optimality can be approached only if there exists information technology (IT) in the availability management process making avail- able accurate inventory data in real time. In this article, we describe an availability management s i m u l a t i o n t o ol t h a t e s t i m a t e s t h e a c c u r a c y o f s h i p date commitment at the presence of imperfect IT environment, which results in inaccurate view of available inventory. Determination of promised ship date is based on availability (inventory) information kept in a computer system (system inventory), which is assumed to be accurate. In actuality, the system inventory and the actual inventory (physical inventory) are synchronized only periodically due to various reasons such as IT costs for the data synchronization, inventory loss, transac- WLRQHUURUDQGLQFRUUHFWSURGXFW LGHQWL¿FDWLRQ The error between the system inventory and the physical inventory could accumulate over time and is not corrected until the refresh of availability (synchronization of inventory), which takes place only periodically (for example, once a day, or a few times a day) since it is expensive to generate new snapshot of availability that are consistent throughout various corporate business systems including ERP (Enterprise Resource Planning) system. In fact, inventory inaccuracy has been LGHQWL¿HGDVDOHDGLQJFDXVHIRURSHUDWLRQDOLQHI- ¿FLHQF\LQVXSSO\FKDLQPDQDJHPHQW$UHFHQW study (DeHoratius & Raman, 2004) shows that WKHYDOXHRIWKHLQYHQWRU\UHÀHFWHGE\WKHVHLQDF- curate records amounts to 28% of the total value of the on-hand inventory for a leading retailer in the U.S. There have been studies on impact of inventory inaccuracy on supply chain performance, includ- ing Iglehard and Morley (1972), Wayman (1995), Krajewski, King, Ritzman, and Wong (1987) and Brown Brown, Inman, and Calloway (2001). More recently, Kang and Koh (2002) simulated the ef- fect of inventory shrinkage (thus inaccuracy) in an inventory replenishment system with an (s, S) policy. Kang and Gershwin (2004) and Kök and Shang (2004) developed methods to compensate for the inventory inaccuracy in replenishment. Fleisch and Tellkamp (2005) analyzed the im- pact of various causes of inventory discrepancy between the physical and the information system inventory on the performance of a retail supply chain based on a simulation model. Our work also studies the impact of inventory inaccuracy, but on accuracy on ship date commitment through a discrete-event simulation modeling approach. Discrete-event simulation has been around for many years in simulating supply chain man- agement (SCM) processes to evaluate its effec- tiveness. McClelland (1992) used simulation to study the effect of MPS method, variability of demand/supplier response on customer services, order cycle, and inventory. Hieta (1998) analyzed the effect of alternative product structures, alter- native inventory and production control methods on inventory and customer service performance. Bagchi, Buckley, Ettl, and Lin (1998) evaluated the design and operation of SCM using simulation and optimization, analyzed SCM issues such as site location, replenishment policies, manufacturing policies, transportation policies, stocking levels, lead time, and customer services. Yee (2002) analyzed the impact of automobile model and option mix on primary supply chain performance such as customer wait time, condition mismatch and part usage. Lee, Cheng, and Leung (2004) simulated the impact of RFID on supply chain performance. However, there has not been any simulation modeling work that analyzes the impact of IT system on the supply chain performance. Development of simulation model for supply chain such as availability management process can be time-consuming. We hope that the simulation- modeling framework we describe in this article can be easily adapted to simulate various avail- ability management situations in many business 623 Balancing Accuracy of Promised Ship Date and IT Costs environments. The simulation framework has been used in IBM for several years, and has been playing a critical role in making strategic busi- ness decisions that impacted customer services DQGSUR¿WDELOLW\LQ,%0 The rest of chapter is organized as follows. In the next section, we describe the availability management process. In the following section, we describe how ship date promising is simulated in various availability refresh frequency. Then, we describe simulation experiments done for IBM’s server business, its impacts and results. Finally, we provide conclusion and remarks. AVAILABILITY MANAGEMENT PROCESS The availability management typically consists of three main tasks: (1) generating availability outlook, (2) scheduling customer orders against WKH DYDLODELOLW\ RXWORRN DQG IXO¿OOLQJ WKH orders. The process described here is based on IBM’s hardware businesses. For certain business, customer orders arrive without any advance no- WLFHUHTXHVWLQJDVHDUO\SRVVLEOHIXO¿OOPHQWRI the orders, usually in a few days. For some other businesses, on the other hand, customers place orders in advance of their actual needs, often a few months in advance. Typically, this kind of customer places orders as early as 3 months before the requested delivery (due) dates, and early de- livery and payment are not allowed. Many buyers in this environment purchase products based on DFDUHIXO¿QDQFLDOSODQQLQJDQGWKH\W\SLFDOO\ know when they want to receive the products and make payment. Generation of availability outlook, is a push- side of the availability management process, and it pre-allocates ATP quantities, and prepares searchable availability database for promising future customer orders. For certain business, availability outlook is generated by daily buckets, and the availability planning horizon goes out a few weeks into the future. For some other busi- nesses, the availability outlook is allocated by weekly buckets, and the availability is planned in a much longer horizon, often a quarter (3 months) into the future. ATP quantity is called Availability Outlook for this reason. The availability outlook is typically generated based on product type, demand classes, supply classes, and outlook time EXFNHWV7KHSURGXFWW\SHFDQEH¿QLVKHGJRRGV (FG) level for Make-to-Stock (MTS) business or components (Comp) level for Make-to-Order 072RU&RQ¿JXUHGWR2UGHU&72EXVLQHVV Demand classes can be geographic sales locations, sales channels, customer priority, sensitivity to GHOLYHU\GDWHVSUR¿WDELOLW\DQGGHPDQGTXDQWLW\ Supply classes can be a degree of constraints and value of products. Availability is pre-allocated into Availability Outlook buckets based on the dimen- sion described earlier, and rolled-forward daily or weekly. The availability outlook is determined EDVHGRQWKHDYDLODELOLW\RIFRPSRQHQWV¿QLVKHG goods, WIP (work-in-process), MPS (master production schedule), supplier commitment, and SURGXFWLRQ FDSDFLW\ÀH[LELOLW\ :KHQ FXVWRPHU orders arrive, the availability outlook is searched in various ways according to scheduling polices to determine the ship (delivery) date, which is then promised to customers. Customer order scheduling is a pull-side of availability management, and it reacts to cus- tomer orders and determines ship date for the orders. Customer orders arrive with various information such as product type, the demand class, customer class, and due date. The order scheduler then searches through the availability RXWORRNGDWDEDVHDQGLGHQWL¿HVWKHDYDLODELOLW\ that meets the characteristics. The scheduling can also be done by an ATP engine that uses certain algorithm to optimize the scheduling consider- ing various resources, policies, and constraints. 7KHVFKHGXOHUWKHQUHVHUYHVVSHFL¿FDYDLODELOLW\ against each order, and decrements the availability according to the purchase quantity of the order. The ship date of the order is determined from . freedom is not the focus here. This work was previously published in Electronic Commerce: Concepts, Methodologies, Tools, and Applications, edited by A. Becker, copyright 2008 by Information Science. coordinate and balance the push-side and pull-side of ATP, and to have adequate Informa- tion System (IS) capability so that desirable and accurate ship date is promised to customer and product. inventory and production control methods on inventory and customer service performance. Bagchi, Buckley, Ettl, and Lin (1998) evaluated the design and operation of SCM using simulation and optimization,