Electronic Business: Concepts, Methodologies, Tools, and Applications (4-Volumes) P13 pptx

54 Semantic E-Business data repositories. Pollard (2004) states that knowledge management activities in healthcare center on acquiring and storage of information, and lacks the ability to share and transfer knowl- edge across systems and organizations to support individual user productivity. In addition the data acquired and stored in islands clinical informa- tion systems are in multiple formats. Common vocabulary to represent data and information LVQHHGHGIRUHI¿FLHQWNQRZOHGJHPDQDJHPHQW (Desouza, 2002). The focus has been on building independent applications to make these systems talk to each other. The need is for models to in- tegrate the data and knowledge in these disparate systems for effective knowledge sharing and use (Sittig et al., 2002). To serve the needs, relevant patient-centered knowledge must be accessible to the person supplying care in a timely manner LQ WKH ZRUNÀRZ ,QWHURSHUDELOLW\ VWDQGDUGV RI emerging Semantic Web technologies can en- able health information integration, providing the transparency for healthcare-related processes involving all entities within and between hospi- tals, as well as stakeholders such as pharmacies, insurance providers, healthcare providers, and clinical laboratories. Further research on using Semantic Web technologies is needed to deliver knowledge services proactively for improved decision making. Such innovations can lead to enhanced caregiver effectiveness, work satisfac- tion, patient satisfaction, and overall care quality in healthcare (Eysenbach, 2003). E-Government E-government refers to the use of Internet tech- nologies for the delivery of government services to citizens and businesses (www.Webster-dictionary. RUJGH¿QLWLRQ(*RYHUQPHQW7KHDLPRI(JRY- ernment is to streamline processes and improve interactions with business and industry, empower citizens with the right information, and improve WKHHI¿FLHQF\RIJRYHUQPHQWPDQDJHPHQW*LYHQ that e-government services extend across different organizational boundaries and infrastructures, there is a critical need to manage the knowledge and information resources stored in these disparate systems (Teswanich, Anutariya, & Wuwongse, 2002). Emerging Semantic Web technologies have the ability to enable transparent information and knowledge exchange to enhance e-government processes. Klischewski and Jeenicke (2004) ex- amine the use of ontology-driven e-government applications based on Semantic Web technolo- gies to support knowledge management related to e-government services. Further research to investigate requirements, design and develop systems, and examine success factors for systems development employing Semantic Web technolo- gies for effective knowledge management within e-government services is needed. ORGANIZATIONS AND RESEARCH GROUPS FOSTERING A SEMANTIC EBUSINESS VISION As research in the foundation technologies for the Semantic Web develops, the application of these technologies to enable Semantic eBusiness is of increasing importance to the professional and academic communities. In this section we would like to inform the readers of several organizations that are involved in furthering research related to Semantic eBusiness. Association for Information Systems (AIS) (www.aisnet.org) A professional organization, the Association for Information Systems (AIS) was founded in 1994 to serve as the premier global organization for aca- demics specializing in information systems. This organization has formed several special interest JURXSV6,*VWRSURYLGHVXEVWDQWLDOEHQH¿WVWR,6 students, academics, and practitioners by helping members exchange ideas and keep up to date on common research interests. The following SIGs 55 Semantic E-Business FRQWULEXWHVLJQL¿FDQWO\WRDGYDFLQJ6HPDQWLF eBusiness research: • Special Interest Group on Semantic Web and Information Systems—SIG-SEMIS (www.sigsemis.org): SIG-SEMIS’ goal is to cultivate the Semantic Web vision in IS. The main areas of emphasis in this SIG are: Semantic Web, Knowledge Management, Information Systems, E-Learning, Busi- ness Intelligence, Organizational Learning, and Emerging Technologies. The SIG aims WR³FUHDWHNQRZOHGJHFDSDEOHRIVXSSRUW- ing high-quality knowledge and learning experience concerning the integration” of the above main areas. This integration will provide the participants of the SIG an op- portunity to create and diffuse knowledge concerning the issues of Semantic Web in the IS research community. • Special Interest Group on Agent-Based Information Systems—SIG-ABIS (www. agentbasedis.org): SIG-ABIS aims to DGYDQFH NQRZOHGJH ³LQ WKH XVH RIDJHQW based information systems, which includes complex adaptive systems and simulation experiments, to improve organizational SHUIRUPDQFH6,*$%,6SURPLVHVWR¿OODQ H[LVWLQJJDSLQWKH¿HOGDQGWKHUHIRUHLVPRUH focused on the strategic and business issues with agent technology and less on the artifact itself, such as computational algorithms, which are well investigated by computer science related research groups.” • Special Interest Group on Ontology Driven Information System—SIG-ODIS (aps.cabit. wpcarey.asu.edu/sigodis/): The objective of 6,*2',6LVWRSURYLGH³DXQLI\LQJLQWHU- national forum for the exchange of ideas DERXWWKH¿HOGRIRQWRORJ\DVLWUHODWHVWR design, evaluation, implementation, and study of ontology driven information sys- tems.” In helping develop awareness and foster research about the role and impact of computational ontologies on the design, development, and management of business information systems, SIG-ODIS also strives to build bridges between the IS discipline and other related disciplines, such as computer science, information science, philosophy, linguistics, and so forth, that pursue research in the broad area of computational ontolo- gies. • Special Interest Group on Process Au- tomation and Management—SIG-PAM (www.sigpam.org): SIG-PAM’s objective LVWRDGGUHVVWKH³QHHGRI,6UHVHDUFK- ers and practitioners for information and knowledge sharing in the areas of process design, automation, and management in both organizational and inter-organizational contexts.” The SIG collaborates with other QRWIRUSUR¿WRUJDQL]DWLRQVWKDWKDYHUHODWHG focus on process theories and applications, VXFKDVWKH:RUNÀRZ0DQDJHPHQW&RDOLWLRQ :I0&WKH:RUNÀRZDQG5HHQJLQHHULQJ International Association (WARIA), and the Computer Supported Collaborative Work (CSCW) Conference. Hewlett-Packard (HP) Labs Semantic Web Research (www.hpl.hp.com/ semWeb/) The HP Labs Semantic Web research group recog- nizes that Semantic Web technologies can enable QHZDQGPRUHÀH[LEOHDSSURDFKHVWRGDWDLQWHJUD- tion, Web services, and knowledge discovery. The HP Labs’ investment in the Semantic Web consists of the development of Semantic Web tools (such as Jena, a Java framework for writing Semantic Web applications) and associated technology, comple- mented by basic research and application-driven research. HP is also part of several collaborative ventures, including involvement in W3C initia- tives (RDF and Web ontologies working groups) and European projects (Semantic Web Advanced Development Europe—SWAD-E and Semantic Web-enabled Web Services—SWWS). 56 Semantic E-Business World Wide Web Consortium’s Semantic Web Initiative (www. w3.org/2001/sw/) The main goal of the W3C Semantic Web initiative is to create a universal medium for the exchange RIGDWD³,WLVHQYLVDJHGWRVPRRWKO\LQWHUFRQQHFW personal information management, enterprise application integration, and the global sharing RIFRPPHUFLDOVFLHQWL¿FDQGFXOWXUDOGDWD7KH W3C Semantic Web activity has been established to serve a leadership role in both the design of VSHFL¿FDWLRQVDQGWKHRSHQFROODERUDWLYHGHYHO- opment of enabling technology.” In addition to these organizations, the forma- tion of this new journal, International Journal on Semantic Web and Information Systems, provides an opportunity for the publication and exchange of research discussions of the Semantic Web in the context of information systems. SUMMARY AND RESEARCH DIRECTIONS The realization of representing knowledge-rich processes is possible through the broad develop- ments in the Semantic Web initiative of the World :LGH :HE &RQVRUWLXP :H GH¿QHG 6HPDQWLF H%XVLQHVVDV³an approach to managing knowl- edge for coordination of eBusiness processes through the systematic application of Semantic Web technologies.” Advances in Semantic Web technologies—including ontologies, knowledge representation, multi-agent systems, and the Web services architecture—provide a strong theo- retical foundation to develop system architecture that enables semantically enriched collaborative eBusiness process. Semantic eBusiness architec- ture enables transparent information and knowl- edge exchange and intelligent decision support to enhance online eBusiness processes. Developments in the availability of content and business logic on-demand, through technologies such as Web services, offer the potential to allow organizations to create content-based and logic- driven information value chains, enabling the needed information transparencies for Semantic eBusiness processes. Research is needed to un- derstand how conceptualizations that comprise business processes can be captured, represented, shared, and processed by both human and intel- ligent agent-based information systems to create transparency in eBusiness processes. Further work on these dimensions is critical to the design of knowledge-based and intelligence-driven eBusi- ness processes in the digital economy. Research is also needed in the development of business models that can take advantage of emergent technologies to support collaborative, knowledge-rich processes characteristic of Se- mantic eBusiness. Equally important is the adap- tation and assimilation of emergent technologies to enable Semantic eBusiness processes, and the contribution to organizations’ value propositions. Topics of research directions include the devel- opment of innovative, knowledge-rich business models that enhance collaborations in eBusiness processes, and innovative technical models that enable the vision of Semantic eBusiness. One of our current research initiatives in- volves developing models for the representation of knowledge, using ontologies and intelligent agents for semantic processing of cross-enter- prise business processes over heterogeneous systems. For the Semantic Web to be a vibrant and humane environment for sharing knowledge and collaborating on a wide range of intellectual enterprises, the W3C must include in its Semantic Web initiatives research agenda the creation of policy-aware infrastructure, along with a trust language for the Semantic Web that can represent complex and evolving relationships. REFERENCES Baader, F., Calvanese, D., McGuinness, D., Nardi, D., & Patel-Schneider, P.F. (2002). The description 57 Semantic E-Business logic handbook: Theory, implementation, and applications. Cambridge University Press. Badii, A., & Sharif, A. (2003). Information man- agement and knowledge integration for enterprise innovation. Logistics Information Management, 16(2), 145-155. %HDP++7KHLQ¿QLWHUHVRXUFH&UHDW- ing and leading the knowledge enterprise. The Academy of Management Executive, 12(3). Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. 6FLHQWL¿F$PHULFDQ, (May), 34-43. Chiu, C. (2000). 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Proceedings of the 3 rd International Workshop on Knowledge Manage- ment in E-Government (pp. 199-209), University of Linz and University of Roskilde. Wiig, K.M. (1993). Knowledge management foundations. Schema Press. This work was previously published in International Journal on Semantic Web & Information Systems, Vol. 1, No. 1, edited by A. Sheth and M. Lytras, pp. 19-35, copyright 2005 by IGI Publishing (an imprint of IGI Global). 59 Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 1.5 The Evolution of ERP and its Relationship with E-Business S. A. Alwabel University of Bradford, UK M. Zairi University of Bradford, UK A. Gunasekaran University of Massachusetts - Dartmouth, USA ABSTRACT Every technical invention is initially designed and eventually applied to solve a real-world problem. The evolution of Enterprise Resource Planning (ERP) is no exception. Owing to its well-organised success to effectively integrate isolated multiple INTRODUCTION The rapid change in technology and other skills DGGHGWRFXVWRPHUVUHTXLULQJKLJKO\VSHFL¿FDQG customised products has led to the need for far JUHDWHUFRRSHUDWLRQZLWKLQDQGEHWZHHQ¿UPV This increasing pressure requires companies to explore a reliable mechanism that makes it easier to save, store, and share useful information. Con- sequently, accounting information system (AIS) was developed to offer a good foundation for control information and knowledge to contribute to a company’s success (Wilkinson, 2000). AIS can be, according to Romney and Steinbart (1999) , r efer r e d t o a s a t r a n s a c t i o n p r o c e s s i n g s y s - WHPEHFDXVHLWRQO\GHDOWZLWK¿QDQFLDOGDWDDQG accounting transactions. It was mainly used as a reporting tool to perform functions such as payroll and invoicing. As the power and sophistication of information technology (IT) continue to grow up, the coverage potentials of AIS have become JUDGXDOO\ PRUH LQDGHTXDWH DQG QRW VXI¿FLHQW for business needs (Romney & Steinbart, 1999). With the growing requirements for information RWKHUWKDQ¿QDQFLDOGDWDRUJDQLVDWLRQVEHJDQWR develop additional information systems. However, 60 The Evolution of ERP and its Relationship with E-Business the existence of multiple systems creates various struggles and inadequacies (Romney & Steinbart, 1999). Very often, the same data, for instance a sale record, must be stored by more than one system. Therefore, the term ERP (enterprise resource planning) emerged, which extends AIS to cover areas like product planning, logistics, accounting DQG¿QDQFLDOVHUYLFHVKXPDQUHVRXUFHVDQGVDOHV distribution. ERP or information systems integration in general are doubtlessly among the most central topics arising at the interface of information systems (IS) and accounting within the past 20 \HDUV%KDWWVWDWHVWKDW³%\DFFHVVLQJ enterprise-wide information from databases, IS integration is providing numerous opportunities to coordinate organisational activities by facili- tating communication and information exchange across departments without the need to go up and down the vertical chain of command. The access to timely, accurate and consistent information is crucial in business process improvement and ac- counting. IS integration, through communication networks and database systems, enables organisa- tions to create and sustain process improvement through timely retrieval of consistent and accurate information.” ERP initiated from the large packaged appli- cation software that had been widespread since WKH ¶V$PRQJWKH¿UVW SDFNDJHGEXVLQHVV applications available was material requirement planning (MRP), introduced in the 1960’s and proposed by Joseph Orlicky, who was regarded as the father of MRP in 1960 in the U.S. (Voll- mann, Berry, & Whybark, 1992). During the 1970’s, the MRP packages were extended, and further applications were added (Chung & Snyder, 2000). The extended resulted in the introduction of manufacturing resource planning (MRP II) systems; this development has been continued (Koh, Jones, Saad, Arunachalam, & Gunasekaran, 2000). Moreover, these systems later evolved to enterprise resource planning (ERP) systems, a term coined by the Gartner Research Group in 1992 and the name can probably be derived from the MRP and MRPII systems (Klaus, Rosemann, & Gable, 2000). ERP systems are highly-inte- grated software packages (Holland. Light, & Kawalek, 1999). However, ERP systems, like all information technology, are rapidly chang- ing. During the 1980’s, this was abandoned and replaced by the client-server architectures, and now newly-released Web-enabled versions have become more and more widespread (Markus & Tanis, 2000). This paper will mainly focus on the evolution of ERP in its historical context. 7KLVZLOOEHFODUL¿HGE\¿UVWH[SODLQLQJ053 DQG053,,V\VWHPVDVD¿UVWDQGVHFRQGSKDVH of ERP systems. Moreover, reasons why MRP and MRPII implementation fail as well as their functions and hierarchy will be investigated to get a clear overview of ERP evolution. Second, ERP’s feature, advantages, and disadvantages as well as reasons why ERP implementation fails will be discussed. Last, the relationship between ERP and e-business will be presented. MATERIALS REQUIREMENT PLANNING (MRP) SYSTEMS Materials Requirements Planning (MRP, or MRP-I) system was launched in the mid-1960s and quickly became popular for providing a logi- cal, easily understood method for determining the number of parts, components, and materials needed for the assembly of each end item in pro- duction. As computer power grew and demands for software applications increased, MRP systems evolved to consider other resources besides ma- terials. Software modules were added to include functions such as scheduling, inventory control, ¿QDQFHDFFRXQWLQJDQGDFFRXQWVSD\DEOH MRP-I system is a computer-based system for managing inventory and production schedules. This approach to materials management applies to large job-shop situations in which many prod- ucts are manufactured in periodic lots in several 61 The Evolution of ERP and its Relationship with E-Business processing steps (Bedworth & Bailey, 1987). MRP and Push systems are often used interchangeably. Conceptually, MRP can be viewed as a method for the effective planning of all resources of a manufacturing organisation (Russell & Taylor, 1998). According to Daft (1991), MRP can be GH¿QHGDVD³GHSHQGHQWGHPDQGLQYHQWRU\SODQ- ning and control system that schedules the exact amount of all materials required to support the GHVLUHGHQGSURGXFW´³,WLVDQLQYHQWRU\RUGHULQJ and time-phased scheduling technique, which uses bill of material, inventory data, and the master production schedule to calculate requirements for material and determine when to release the material replenishment order” (Torkzadeh & Sharma, 1991). Thus, for the purpose of this SDSHU053FDQEHGH¿QHGDVDFRPSXWHUEDVHG planning, scheduling, and control system that gives management a tool to plan and control its manufacturing activities and supporting opera- tions obtaining a higher level of customer service while reducing costs. The Purpose of MRP Systems MRP is primarily used for scheduling high-value commissioned parts, materials, and supplies when demand is r easo nably well know n (Bal lou , 1999). Ballou (1999) further states that precise timing of PDWHULDOÀRZVWRPHHWSURGXFWLRQUHTXLUHPHQWVLV the principle behind MRP. According to Chase and Aquilano (1995), the MRP functionality within organisations enables: • full materials planning to ensure the required inputs into the manufacturing process are available to meet demand from order pro- posals; • planning to be carried out for a single item if the MRP controller wants to plan a particular material; and • a bill of materials sequencing the assembly SDUWVRIWKH¿QDOSURGXFW The main function of MRP according to Ballou (1999) is to monitor stocks and to determine which material the company needs, in what quantity, at what time, and to create the corresponding order proposals automatically. In MRP, the sys- tem compares available warehouse stock orders scheduled receipts from purchasing or production with planned requirements in the net requirements calculation. In the case of a material shortage, that is, if available stock is less than the quantity required, the system creates an order proposal (Ballou, 1999). The objectives of MRP are similar to those of any inventory management system. These objec- tives are improving customer service, minimising inventory investment, and maximising production RSHUDWLQJHI¿FLHQF\&KDVH$TXLODQR According to Torkzadeh and Sharma (1991), MRP is an inventory control and production planning system designed for ordering and scheduling dependent demand of inventory, which includes the following components: master schedule, bill RIPDWHULDODQGLQYHQWRU\UHFRUG¿OH Advantages of MRP Systems Material requirements planning (MRP) methods try to avoid, as much as possible, carrying items in inventory through precise timing of material ÀRZVWRPHHWUHTXLUHPHQWV%DOORX,WLV a preferred method when demand is reasonably known due to the uncertainty of the forecasting component. If demand is forecasted to change, MRP planning adapts to this new level of re- quirement. Nahmias (1997) says that MRP may be considered a top-down planning system in that all production quantity decisions are derived from demand forecasts. Coyle, Bardi, and Langley (1996) consider a principal advantage of MRP is the ability to maintain reasonable safety stock levels and minimise or eliminate inventories wherever possible. In addition, other advantages, according to Chase and Aquilano (1995), include the following: 62 The Evolution of ERP and its Relationship with E-Business • identify process problems long before they occur, • base production schedules on actual demand, and • coordinate materials ordering across the ¿UP Disadvantages of MRP Systems Nahmias (1997) states that, in a push system, items are produced based on a plan or forecast and pushed to the next level. Simchi-Levi, Kamin- sky, and Simchi-Levi (2000) state the following problems that are associated with push systems: 1. Push systems are slow to react and some - times even unable to react to changes in the market place. 2. Product obsolescence may occur in a push system as consumer preferences and demand changes for a certain product. 3. Inventory and carrying costs are generally higher in a push system (Simchi-Levi et al., 2000). However, the trade-off in costs associated with MRP concepts is between having the ma- terials arrive before they are needed, in which case they are subject to a holding charge, and the expected cost of the materials arriving after they are needed so the materials are subject to a late charge. According to Ballou (1999), the challenge of scheduling models (MRP) is to determine the optimal time to release the request for materials ahead of requirements. Moreover, a major problem with MRP modelling is that not all uncertainties are taken into account. Uncertainties include changes in demand that were not captured by the forecast and the variance in lead-times. Ballou (1999) further adds that the challenge of MRP is WR¿QGWKHRSWLPDOUHOHDVHWLPHIRUPDWHULDOVWR meet requirements. There is uncertainty associ- ated with the release time as the required time for the transportation component of the supply chain may vary between points. Reasons for the Failures Many authors state that struggles associated with MRP systems to be implemented correctly, to a certain extent, with organisational and behav- ioural factors (Chase & Aquilano, 1995; Turbide, 1995). Yet, it seems to be generally agreed that failure of an MRP installation can be traced to problems such as: Lack of Top Management Commitment MRP system requires a major commitment from top management in order for it to be successful. This means not only the commitment of resources, but also the commitment of top management’s time to ensure the right coordination among the various functions. A well-functioning schedule FDQXVHWKH¿UP¶VDVVHWVHIIHFWLYHO\DQGHI¿FLHQWO\ DQGWKLVLQVHTXHQFHZLOOLQFUHDVHWKH¿UP¶VSURI- its. Thus, MRP should be acknowledged by top management as a planning tool with particular UHIHUHQFH WR SUR¿W UHVXOWV &KDVH  $TXLODQR 1995, p. 595). According to Zairi (2000): The key drivers for adding optimum value to society DQGWKHFRPPXQLWLHVLQZKLFKVSHFL¿FEXVLQHVV organisations operate are through having strong commitment to corporate and social governance, having an open dialogue with external stake- holders and having the determination to achieve environmental sustainability. Intensive Executive Education is Needed In nearly every study conducted, the lack of proper training is considered a key barrier to MRP implementation. Raysman (1981) comments that lack of understanding about systems is frequently quoted as a reason for failure of companies en- deavours. Sum and Yang (1993) recognised that the lack of MRP expertise and training were main problems facing companies to implement 63 The Evolution of ERP and its Relationship with E-Business MRP. In a desire to convert to the new system quickly, there is often an underperformance in the training of personnel at all levels. However, proper training is required from the technical perspective as well as from the users’ perspective. Thus, the IT department within an organisation needs to entirely understand all of the technical characteristics of the system in order to provide the proper support to the business functions that use it. Simultaneously, the business functions need to recognise the different procedures for entering data and producing reports. Too Rigid The aims of the MRP system are to minimising inventory investment and maximising production RSHUDWLQJHI¿FLHQF\&KDVH$TXLODQR thus the accuracy of the recorded levels becomes VLJQL¿FDQW&KDVHDQG$TXLODQRVWDWHWKDW ³3HUKDSVRQHRIWKHELJJHVWFRPSODLQWVE\XVHUV is that MRP is too rigid. When MRP develops a VFKHGXOHLWLVTXLWHGLI¿FXOWWRYHHUDZD\IURP the schedule if need arises.” MANUFACTURING RESOURCE PLANNING (MRPII) SYSTEMS As it was shown, the MRP contains a method for planning and procuring the materials to support production. During years of using MRP, the need for other functions arose that would, together with MRP, create an actually integrated manufactur- ing management system. Thus, it was done by creating a large production control system named manufacturing resources planning (MRPII). 'H¿QLWLRQRI053,,6\VWHPV Manufacturing resource planning (MRPII) sys- WHPLVGH¿QHGE\WKH$PHULFDQ3URGXFWLRQDQG Inventory Control Society (APICS) as a system for the effective planning of all the resources of a manufacturing business (Higgins, Le Roy, & Tierney, 1996). It is a direct successor of the material requirements planning (MRP). MRPII LVFRQFHUQHGZLWKPDQDJLQJWKHÀRZRIPDWHULDO into, through, and out of the organisation (Arnold, 1998). Thus, MRPII is a system in which the en- tire production environment is evaluated to allow master schedules to be adjusted and created based on feedback from current production/purchase conditions (Bedworth & Bailey, 1987). Functions of MRPII Systems The functions of MRPII according to Higgins et al. (1996) can be summarised as follows: • 7KHRSHUDWLRQDQG¿QDQFLDOV\VWHPDUHWKH same. • It has simulation capabilities that enable predictions to be made beforehand. • It involves every facet of business from plan- ning to execution (Higgins et al., 1996). Although MRPII is an imposing tool when used properly, there are some considerations that must be addressed for it to function effectively. • 7KHIXQFWLRQVZLWKLQD¿UPPXVWEHLQWH- grated. They must agree on what is being produced and in what quantities. Often, organisational boundaries are crossed when these decisions are being made. • Stringent data requirements are needed for MRPII to function properly. Errors in data FDQEHPDJQL¿HGJUHDWO\E\WKHSURFHVV • It is extremely important that feedback from the process is monitored regularly. Informa- tion that is shared among functions can help to reduce errors, especially with lead times (Kessler, 1991). . activities in healthcare center on acquiring and storage of information, and lacks the ability to share and transfer knowl- edge across systems and organizations to support individual user. implementation, and study of ontology driven information sys- tems.” In helping develop awareness and foster research about the role and impact of computational ontologies on the design, development, and. automation, and management in both organizational and inter-organizational contexts.” The SIG collaborates with other QRWIRUSUR¿WRUJDQL]DWLRQVWKDWKDYHUHODWHG focus on process theories and applications,