1034 Measurements in E-Business EMERGING ISSUES IN E-BUSINESS MEASUREMENTS Online interviewing and focus groups. Purely quantitative analyses of clickstream data and Internet survey research methods are limited in their abilities to enlighten us. Web surveys have notoriously low response rates, and are often suspect in their abilities to gather a representative sample (Dillman, 2000). Simple frequency counts of consumer actions yield very shallow data. Since technology has sped up the transmission of Internet content, and advances in software have dramatically enhanced Web design and graphics, researchers have expanded the use of online quali- tative research. For instance, it is not uncommon to hold online focus groups wherein respondents can interactively participate in virtual forums. Participants can evaluate prototypes, respond to potential advertisements, and hold meaningful, insightful conversations about various aspects of e-business. Furthermore, online interviewing is growing in popularity. This is a way to effectively reach some very narrow groups of respondents and gather very rich, powerful data. Online LQWHUYLHZVDOVRDOORZIRUJUHDWHUÀH[LELOLW\IRO- low-up questions, and provide greater depth of analysis. Qualitative Internet research is certainly DQHPHUJLQJ¿HOG Content analysis. Again, as advances in technology, hardware, and software progress, researchers have begun to analyze Internet con- tent more directly and more precisely (Boush & Kahle, 2004). The essence of content analysis is to measure words and phrases throughout a page, a site, a chatroom, a blog, and so forth. Researchers have detected meaningful patterns in the data, PDGH¿WWLQJLQWHUSUHWDWLRQVDQGGHULYHGVWUDWHJLF insights for future actions. Researchers have even coined a new phrase to describe the word-of-mouth communication over the Internet. Dubbed word on-line (WOL), researchers have noted the pow- HUIXOLQÀXHQFHRIWKHRQOLQHFRPPXQLW\DQGWKH ever-expanding number of conversations (Granitz & Ward, 1996). Continuing challenges in electronic survey research. As technological advances make elec- tronic survey research easier, faster, and cheaper, a number of challenging issues arise. First, the issue of low response rates must be addressed. Surely a nonresponse bias must be affecting some research results. Second, asking the right questions and recording the right answers from the right respondents has become increasingly GLI¿FXOW:HFDQQRWVLPSO\FRQWLQXHWRPDNHXS in quantity of data what we knowingly lack in quality of data. We must strive to keep e-business research meaningful and strategically useful. Fi- nally, we must develop a viable communications framework that encompasses the interactivity of e-business, the informational asymmetry that abounds, as well as the unique perspectives of Internet users and e-businesses. Within a sound framework, valid, reliable, and relevant metrics will emerge as the new standard. Future research. The emergence of the Internet as the foundation for business communications worldwide has given rise to a wealth of truly spec- tacular measurement tools. Business researchers now have access to an abundance of data that, just a few years ago, might have been deemed un- imaginable. Furthermore, they have the research tools to analyze and interpret mass quantities of information; thereby, giving valuable meaning to seemingly chaotic data. Researchers can now track consumer responses and measure psychological issues in a multitude of forms. Straub, et al. (2002) not only provide an expert synopsis of existing metrics, but also provide excellent foresight into numerous e-business metrics that require further exploration, examination, and validation. The OLNHO\³QH[WVWHS´LQRQOLQHEXVLQHVVPHWULFVZLOO be the measurement of the Internet consumption experience. Some major research questions arise, including (1) What makes the Internet consump- tion experience so different? (2) Which off-line behavioral/communications/business theories 1035 Measurements in E-Business apply to the online context and which need to be altered? (3) What information processing and decision-making theories apply to the CME? (4) Which metrics apply to the online business-to- business context? REFERENCES Aiken D., Liu, B., Mackoy, R., & Osland, G. (2004). Building Internet trust: Signaling through trustmarks. International Journal of Internet Marketing and Advertising, 1(3), 1-17. Bakos, Y. (1997). Reducing buyer search costs: Implications for electronic marketplaces. Manage- ment Science, 43(12), 1676-1692. Bakos, Y. (1998). The emerging role of electronic marketplaces on the Internet. Communications of the ACM, 41(8), 35-42. Benassi, P. (1999). TRUSTe: An online privacy seal program. Communications of the ACM, 42(2), 56-59. Bettman, J., Johnson, E., & Payne, J. 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KEY TERMS Click-Stream: The series of links that a user goes through when using the Internet (Rayport & Jaworski, 2002). Cognitive Effort: Information load that deals with how cognitive processes handle incoming stimuli (information) (Bettman et al., 1990). Conversion Rates: A frequency measure- ment of the completion of some action(s) by an e-consumer as a proportion of the total number of visitors to site (Bhat et al., 2002; Rayport & Jaworski, 2002). Flow: The state during Web navigations char- acterized by (1) a seamless sequence of responses facilitated by interactivity, (2) an intrinsically enjoyable experience, (3) accompanied by a loss of self-consciousness that is (4) self-reinforcing (Novak, et al., 2000). Stickiness: Sometimes a subjective/attitudinal measurement of how attractive and memorable a site is (Gladwell, 2000). Stickiness can also be evaluated according to the frequency of Web-site visits and the average time spent per visit (Bhat et al., 2002). This work was previously published in Handbook of Research on Electronic Surveys and Measurements, edited by R. Reynolds; R. Woods; J. Baker, pp. 416-424, copyright 2007 by Information Science Reference (an imprint of IGI Global). 1038 Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 4.5 Electronic Policing: A Framework for Crime Control and Citizen Services Roongrasamee Boondao Ubon Rajathanee University, Thailand Nitin Kumar Tripathi Asian Institute of Technology, Thailand ABSTRACT This chapter examines electronic policing (e- policing), which has played an increasing role in government-management reform and has become an important area for e-government research. Firstly, the strategic framework and develop- ment of e-policing are reviewed. A framework of mobile policing is introduced that is derived from the system requirements of both police and citizens. We examine how an e-policing system is implementing this framework for improving the HIIHFWLYHQHVVDQGHI¿FLHQF\RIFULPHFRQWURODQG also providing services to citizens. The system not R Q O\ VL PSO L ¿ HV W K H FRO OH FW LR Q VW RU D J H D Q GU HW U L H YD O of crime data but also uses Bayesian analysis to JLYHFRQVWDQWO\UH¿QHGSUHGLFWLRQVRIWKHULVNVRI crime in different localities, along with the factors LQ ÀXHQFLQJWKHU LVNOHYHOV)LQDOO\HYDOXDWLRQVRI the system are discussed. User evaluations of the system allowed us to study the potential of the system for crime control and citizen services. INTRODUCTION Public administrative work has characteristics that distinguish it from business. The public sector provides a wide range of services to so- ciety that are different from those provided by EXVLQHVV¿UPV7KHJRYHUQPHQWXVHVLQIRUPD- tion and communication technology to improve HIIHFWLYHQHVVDQGHI¿FLHQF\WRPHHWWKHUHTXLUH- ments of new forms of government management and accountability and to satisfy the demand of external agencies for information. E-government FDQIDFLOLWDWHPRUHHI¿FLHQWDQGHIIHFWLYHDS- plications of e-business principles, which could provide citizens, employees, government agencies and businesses with more convenient access to 1039 Electronic Policing: A Framework for Crime Control and Citizen Services government information and services (Hernon, Reylea, Dugan, & Cheverie, 2002). Police work can be viewed as being representative of govern- PHQWZRUNDVSROLFHRI¿FHUVPXVWSURYLGHPDQ\ critical services to citizens, ranging from policing duties (law enforcement, crime prevention, crime investigation, etc.) to nonpolicing duties (search and rescue, public relations, etc.). To modernize police work, a number of researchers and police agencies have emphasized the use of information and communication technology to improve ef- IHFWLYHQHVVHI¿FLHQF\DQGWUDQVSDUHQF\PDNLQJ police work more citizen centered and assisting in local problem-solving initiatives to reduce crime and ensure public safety (Lincolnshire Police, 2003; Liu & Hu, 2005; 3DFL¿F&RXQFLORQ,QWHU- national Policy (PCIP), 2002; Police Information Technology Organization (PITO), 2002; Spicer & Mines, 2002; Sussex Police, 2003; Woods, 2001). Crime control is one vital police task that is still problematic from a number of aspects. There is the problem of organizing the crime investigation SURFHVV3ROLFHKDYHGLI¿FXOWLHVLQcrime inves- tigation. They need support from witnesses. In order to motivate the public to interact with police agencies, police need to provide crime information and also convenient methods of communication. There have been a number of research studies and police projects relating to e-policing and crime control. E-policing strategic frameworks also have attracted the attention of police policy makers (Lincolnshire Police, 2003; Spicer & Mines, 2002; Sussex Police, 2003). A number of researchers have covered particular aspects of the application of information communication technology (ICT) to police work, such as information sharing and monitoring (Chen et al., 2003; Falcon, 1998; Zeng, Chen, Hsinchun, Daspit, Shan, Nandiraju, Chau, & Lin, 2003), forensic evidence (Smith, Puch, Wynn, Bates, Evett, & Champod, 2002), burglary prediction (Oatley & Ewart, 2003), crime knowl- edge management (Pendharkar & Bhaskar, 2003) and geographic information systems (GIS) for crime analysis and monitoring (Bowers, Newton, & Nutter, 2001; Costello & Wiles, 2001; Gupta, 2001; Rich, 1999). However, in addition to crime control, police agencies also provide other services to citizens. Most of the studies and projects cited focus on only a particular aspect of police opera- tions, without considering citizen services. In this chapter, we report on our experience in designing and evaluating an integrated system for crime control and citizen services. This ap- proach was implemented in a prototype system. The prototype system provides wireless GIS to support police work and also services to citizens. In addition, the research developed a Bayesian network model for analysis of the factors affect- ing crime risk. This chapter is organized into four VHFWLRQV³%DFNJURXQG´RIHSROLFLQJLVDUHYLHZ of e-policing systems development with research TXHVWLRQV IURP WKLV VWXG\ RXWOLQHG ³0RELOH Policing Framework” provides insight into the development of the framework, the application scenarios of the system, system evaluation and LPSOLFDWLRQVIRUSUDFWLFH³)XWXUH7UHQGV´FRQ- siders developments in technology and areas for IXUWKHUVWXG\DQGWKH³&RQFOXVLRQ´ BACKGROUND 'H¿QLQJ(3ROLFLQJ 'H¿Q LW LRQ VRIHS ROLFL QJDERX QGL QWKHOLW HUDW XU H 7KHIROORZLQJGH¿QLWLRQVFKDUDFWHUL]HHSROLFLQJ in a variety of ways. • E-policing refers to the use of the Internet to deliver police services to the public. A Web site, e-mail and fax are contact methods that the public can use in addition to the telephone and face-to-face channels. The ideal is to provide consistent citizen access irrespective of the access channel that is being used (Sussex Police, 2003). 1040 Electronic Policing: A Framework for Crime Control and Citizen Services • The use of the computer (including digital telephony) technologies to deliver police services (Lincolnshire Police, 2003). • E-policing focuses on the needs of the IURQWOLQHSROLFHRI¿FHUDQGWKHSXEOLF7KH exploitation of new technology will sup- port the provision of an infrastructure and communications network to facilitate get- ting information and services to the right person at the right time in the right place, ZKHWKHUWRDFLWL]HQRUSROLFHRI ¿FH UD VZHOO as providing choice for the public (Spicer & Mines, 2002). • E-policing is the use of ICT in police work WRLPSURYHHIIHFWLYHQHVVDQGHI¿FLHQF\ VXSSRUWIURQWOLQHRI¿FHUVDQGDVVLVWLQORFDO problem-solving initiatives to reduce crime and reassure the public (Woods, 2001). In practice, police work covers a wide range of functions. Goldstein (1977) has categorized these as follows: • To prevent and control conduct widely recog- nized as threatening to life and property • To aid individuals who are in danger of physical harm, such as the victims of violent attacks • To facilitate the movement of people and vehicles • To assist those who cannot care for them- selves—the intoxicated, the addicted, the mentally ill, the physically disabled, the old and the young • 7R UHVROYH FRQÀLFW ZKHWKHU LW EH DPRQJ individuals, groups or individuals, or indi- viduals and their government • To identify problems that have the potential for becoming more serious problems • To create and maintain a feeling of security in communities The Working Group on E-Government in the Developing World, under the auspices of the 3DFL¿F &RXQFLO RQ ,QWHUQDWLRQDO 3ROLF\ OLVWHG the following as broad categories of goals for e-government (PCIP, 2002): • Improving services to citizens • Improving the SURGXFWLYLW\DQGHI¿FLHQF\ of government agencies • Strengthening the legal system and law enforcement • Promoting priority economic sectors • Improving the quality of life for disadvan- taged communities • Strengthening good governance and broad- ening public participation It can be readily seen that a number of these goals can be effectively applied to e-policing. E- policing can employ numerous features of local e-government as the building blocks for service delivery, such as acknowledging that it is impor- tant to provide to the public appropriate services electronically 24 hours a day, 7 days a week (Spicer & Mines, 2002). ICT has played an important role in providing support for police functions. E-policing has huge potential in both developed and developing countries. Internet technology is expected to enhance police services in terms of FRQYHQLHQFHDQGFRVWHI¿FLHQFLHVWKDWZLOOJLYH the public increased choice when deciding how to use police services and help build a new police VHUYLFHWKDW¿WV st century needs (Woods, 2001). A number of e-policing strategic frameworks have been proposed as ways of delivering e-policing. In England, most e-policing strategic frame- works have been produced in response to the government’s White Paper on Modernizing *RYHUQPHQWZKLFKOLVWVWKHREMHFWLYH³%\ all services (with exclusions for policy or opera- tional reasons) should be available electronically” (Lincolnshire Police, 2003; Spicer & Mines, 2002; Sussex Police, 2003). In addition, the police agencies follow the Police Information Technol- ogy Organization (PITO) national e-policing strategic framework. As an important part of the 1041 Electronic Policing: A Framework for Crime Control and Citizen Services e-government initiative in the U.K., the e-polic- ing program was introduced to revolutionize the police service and improve the effectiveness of crime prevention and detection by providing the following (PITO, 2002): • Ready access for the public to police informa- tion and services through a variety of easy to use, safe and secure channels, including the use of intermediaries; • Provision of information and services of relevance to the citizen, particularly victims RIFULPHLQDWLPHO\DQGHI¿FLHQWPDQQHU • Support for cooperative working across police forces and with other criminal justice agencies and local authorities; • Better use of information across all forces and with other criminal justice agencies to support the implementation of the National Intelligence Model and to make policing more effective in combating criminality; • The collection, exchange and storage of information in a secure and trusted environ- ment; and • Flexibility to accommodate new business requirements and to take advantage of changes in technology. Development of E-Policing Most police agencies have developed their own information technology (IT) systems to support their work. Primarily, these IT systems can be grouped into categories based on the particular applications for which they were developed. Examples of each type from the literature are reviewed here under the following categories: information sharing and monitoring, intelligent crime analysis and GIS for crime analysis and monitoring. Information sharing and monitoring. Information sharing and monitoring are especially important for crime analysis and investigation. Timely ac- cess to information is often critical. With rapid advancement of IT and the Internet, researchers and police agencies have paid special attention to developing such systems. Future Alert Contact Network (Falcon, 1998) is a community-based policing system. It offers the functionality of monitoring all incoming records relevant to a UHTXHVW DQG WKHQ QRWL¿HV DQ RI¿FHU E\ HPDLO or pager when the request is met. COPLINK Connect system (Chen et al., 2003) enables law enforcement agencies to search for information more effectively by providing an interface that integrates data from various sources, including incident records, mug shots and gang information. COPLINK Agent (Zeng et al., 2003) is designed to SURYLGHDXWRPDWLFLQIRUPDWLRQ¿OWHULQJDQGPRQL- toring functionalities. The system also supports knowledge sharing by proactively identifying RI¿FHUVZKRDUHZRUNLQJRQWKHVDPHRUVLPLODU cases on a real-time basis. Intelligent crime analysis. T he adding of an intel- ligent component to crime analysis is one of the most attractive areas to researchers. Some intel- ligent techniques, such as Bayesian networks, and neuron networks have been applied to crime analysis. Smith et al. (2002) developed an inferen- tial framework for a future custom-built decision support system to help forensic scientists perform their sometimes delicate and nonstandard tasks. A system would be particularly helpful for sci- entists who investigate forensic evidence arising from high-volume crime, such as the burglary of electronic equipment, which frequently occurs and shares many qualitative features. Oatley and Ewart (2003) undertook a study making use of both historical and contemporaneous informa- tion to generate a burglary prediction system. 7KHLU SDSHU GHWDLOHG KRZ WKH ¿QDO SUHGLFWLRQV on the likelihood of burglary were calculated by combining all of the varying sources of evidence into a Bayesian belief network and the issues surrounding the construction of such a model. Pendharkar and Bhaskar (2003) proposed an ap- 1042 Electronic Policing: A Framework for Crime Control and Citizen Services proach for building a hybrid Bayesian network based on a multiagent system for drug crime knowledge management. They used distributed DUWL¿FLDO LQWHOOLJHQFH DUFKLWHFWXUH WR FUHDWH D multiagent information system that integrated distributed knowledge sources and information to aid decision making. GIS for crime analysis and monitoring. GIS have been adopted by police forces for use in several areas, such as crime pattern analysis, repeat vic- timization and crime monitoring. Bowers et al. (2001) developed a GIS-based database application WRDVVLVWLQWKHLGHQWL¿FDWLRQRIYXOQHUDEOHWDUJHWV for a domestic-dwelling, target-hardening scheme. 7KHLUV\VWHPXVHGGH¿QHGFULWHULDWRSULRULWL]H recent victims of burglary. This prioritization system produced targeting information on a daily basis. Costello and Wiles (2001) used geocoded crime data to look at the patterns produced by analyzing the location of offenses and the resi- dential addresses of offenders and victims, and the relationships between the locations linked by offenses. Gupta (2001) developed a GIS routine to help police to correlate, visualize and analyze crime data. The crime picture becomes crystal clear, thereby improving police management. Rich (1999) illustrated that mapping can be used for WUDFNLQJGU XJÀRZLQWRWKH8QLWHG6WDWHVDQGODZ enforcement areas. However, in these cases, GIS ZDVXVHGLQDSSOLFDWLRQVVXLWDEOHIRURI¿FHZRUN ZLWKRXWZLUHOHVVDFFHVVIRUSROLFHLQWKH¿HOG Research Questions Each of the above systems focuses on only certain aspects of police operations but does not consider services to citizens. The goal of the system de- veloped here is to provide an integrated solution to crime control and the provision of services to citizens. Effective crime control requires the col- lection, organization and retrieval of a variety of data. Multiple types of data, such as text (crimi- nal data, property data, gang information, case information), graphic (photographs of criminals, pictures of crime scenes) and geographic data (crime locations, details of the area), need to be accessed when and where they are needed, espe- cially in time-critical situations. A new trend in technology, wireless access devices like personal digital assistants (PDAs) and mobile telephones are among the most important technologies to support e-policing initiatives. Since people tend to carry their mobile devices with them wherever they go, they remain linked to the Internet at all times, not only when sitting at a desk in front of a computer. Therefore, police agencies need to plan for a massive change in the way many of the public use the Internet and interact with each other and with agencies. A police agency also needs to look for ways to utilize wireless technol- RJ\WRLPSURYHWKHHIIHFWLYHQHVVDQGHI¿FLHQF\ of the delivery of core operations and in doing VRKHOSWKHSXEOLF3ROLFHRI¿FHUVVSHQGDORWRI their time patrolling the streets and investigating crimes. To accommodate this mobility, wireless access is important. Geographical locations play an important role in crime control. It would be of YDOXHWRWKHSROLFHRI¿FHUVWRDFFHVVJHRPDSSLQJ data anywhere and at anytime. For this research a Bayesian network model was developed to analyze the factors affecting crime risk. The objective of this study was to answer these three important research questions: • How can e-policing services be integrated to serve communities better? • How will such a system support police of- ¿F HU VL QW KH L U FU L PH FR QW U R O D QG L Q Y H V W LJ D W L Y H work? • How will the system support citizens in obtaining services from police agencies? 1043 Electronic Policing: A Framework for Crime Control and Citizen Services MOBILE POLICING FRAMEWORK Architecture of a Mobile Police System Here we propose a framework for an integrated wireless GIS to support crime control and provide services to citizens. The design of the framework w a s g u i d e d b y u s e r r e q u i r e m e n t s f r o m b o t h p o l i c e and citizens that were obtained through structured questionnaires and interviews. The proposed ar- chitecture of the system is illustrated in Figure 1. The system consists of a user interface, a database management system (DBMS), which contains VSDWLDODQGQRQVSDWLDOGDWDEDVHDQG¿YHIXQFWLRQDO modules, namely the wireless GIS module, crime factor analysis module, reporting and searching module, location-based system (LBS) module and security module. The functionality of each module is described below. Wireless GIS module. The wireless GIS module is used to develop real-time crime data access to KHOSWKHSROLFHWREHPRUHHIIHFWLYHDQGHI¿FLHQW in crime control and also provide services to citizens. The wireless GIS with integration of technologies, such as global positioning systems (GPS), digital photography, digital videography and databases, is used for developing the functions of crime recording, updating and representing crime-map data. The system consists of mobile devices capable of accessing the Internet with proper extensions for a GPS receiver and compact ÀDVK FDPHUD'DWDFDQ EHVLPSO\ORJJHGIURP the crime scenes and uploaded to a geo-database server. OpenGIS enables spatial data sharing and system interoperability, leading to data integrity and timeliness and reduced data replication. Open source software and freeware packages, such as Minnesota MapServer, PostgreSQL and PostGIS, were used to develop the system (Boondao, Es- ichaikul, & Tripathi, 2004a). Crime factor analysis module. The crime factor analysis module (Boondao, Esichaikul, & Trip- athi, 2004b) was developed based on the crime pattern analysis of Brantingham and Branting- ham (1991) and theory of crime control through environmental design (Jeffery, 1971; Rhodes & Conly, 1991). Pattern theory focuses attention and research on the environment and crime and insists that crime locations, characteristics of such locations, the movement paths that bring offenders and victims together at such locations and people’s perceptions of crime locations are VLJQL¿FDQW REMHFWV IRU VWXGLHV 3DWWHUQ WKHRU\ synthesizes its attempt to explain how changing VSDWLDODQGWHPSRUDOHFRORJLFDOVWUXFWXUHVLQÀX- Figure 1. Architecture of a mobile police system PDA User Interface G2E, G2C, G2G Wireless GIS Module Security Module Reporting and Searching Module Crime Factor Analysis Module Crime data GIS data DBMS Mobile Phone Internet LBS Module . crime analysis and GIS for crime analysis and monitoring. Information sharing and monitoring. Information sharing and monitoring are especially important for crime analysis and investigation EXVLQHVV¿UPV7KHJRYHUQPHQWXVHVLQIRUPD- tion and communication technology to improve HIIHFWLYHQHVVDQGHI¿FLHQFWRPHHWWKHUHTXLUH- ments of new forms of government management and accountability and to satisfy the demand of external. government agencies and businesses with more convenient access to 1039 Electronic Policing: A Framework for Crime Control and Citizen Services government information and services (Hernon,