Examining Technology Adoption and Management Perception of Inventory Management Systems: The Case of Aruba Restaurants

The purpose of this paper is to explore the use of automated inventory management systems (IMS) and identify the stage of technology adoption for restaurants in Aruba. A case study analysis involving twelve members of the Aruba Gastronomic Association was conducted using a qualitative research design to gather information on approaches currently used as well as the reasons and perceptions managers/owners have for using or not using automated systems in their facilities. This is the first study conducted using the Aruba restaurant market. Therefore, the application of two technology adoption models was used to integrate critical factors relevant to the study. Major findings indicated the use of an automated IMS in restaurants is limited, thus underscoring the lack of adoption of technology in this area. The results also indicated that two major reasons that restaurants are not adopting IMS technology are budgetary constraints and service support. This study is imperative for two reasons: (1) the results of this study can be used as a comparison for future IMS adoption, not only for Aruba’s restaurant industry but also for other Caribbean destinations and the U.S., (2) this study also provides insight into the additional training and support help needed in hospitality technology services.

Factors Affecting the Adoption of New Technology: the case of 311 Government Call Centers

Government call centers (311) were first created to reduce the volume of non-emergency calls that were being placed to emergency 911 call centers. The number of 311 call centers increased from 57 in 2008 to about 300 in 2013. Considering that there are over 2,700 municipal government units across the United States, the adoption rate of the 311 centers is arguably low in the country. This dissertation is an examination of the adoption of 311 call centers by municipal governments. My focus is specifically on why municipal governments adopt 311 and identifying which barriers result in the non-adoption of 311 call centers. This dissertation is possibly the first study to examine the adoption of 311 call centers in the United States. The dissertation study has identified several significant factors in the adoption and non-adoption of 311 government call centers. The following factors were significant in the adoption of 311 government call centers: managerial support, financial constraints, organizational responsiveness, strategic plan placement, and technology champion. The following factors were significant barriers that resulted in the non-adoption of a 311 government call center; no demand from citizens, start up costs, annual operating costs, unavailability of funding, and no obvious need for one.If local government entities that do not have a 311 government call center decide to adopt one, this study will help them identify the conditions that need to be in place for successful adoption to occur. Local government officials would first need to address the barriers in setting up the 311 call centers.

Factors affecting the adoption of new technology: The case of 311 government call centers

Government call centers (311) were first created to reduce the volume of non-emergency calls that were being placed to emergency 911 call centers. The number of 311 call centers increased from 57 in 2008 to about 300 in 2013. Considering that there are over 2,700 municipal government units across the United States, the adoption rate of the 311 centers is arguably low in the country. This dissertation is an examination of the adoption of 311 call centers by municipal governments. My focus is specifically on why municipal governments adopt 311 and identifying which barriers result in the non-adoption of 311 call centers. This dissertation is possibly the first study to examine the adoption of 311 call centers in the United States. ^ The dissertation study has identified several significant factors in the adoption and non-adoption of 311 government call centers. The following factors were significant in the adoption of 311 government call centers: managerial support, financial constraints, organizational responsiveness, strategic plan placement, and technology champion. The following factors were significant barriers that resulted in the non-adoption of a 311 government call center; no demand from citizens, start up costs, annual operating costs, unavailability of funding, and no obvious need for one. ^ If local government entities that do not have a 311 government call center decide to adopt one, this study will help them identify the conditions that need to be in place for successful adoption to occur. Local government officials would first need to address the barriers in setting up the 311 call centers. ^

The adoption of retail electronic commerce: An empirical investigation

The purpose of this study was to empirically investigate the adoption of retail electronic commerce (REC). REC is a business transaction which takes place over the Internet between a casual consumer and a firm. The consumer has no long-term relationship with the firm, orders a good or service, and pays with a credit card. To date, most REC applications have not been profitable. To build profitable REC applications a better understanding of the system's users is required. ^ The research model hypothesizes that the level of REC buying is dependent upon the Buying Characteristics of Internet Use and Search Experience plus the Channel Characteristics of Beliefs About Internet Vendors and Beliefs About Internet Security. The effect of these factors is modified by Time. Additional research questions ask about the different types of REC buyers, the differences between these groups, and how these groups evolved over time. ^ To answer these research questions I analyzed publicly available data collected over a three-year period by the Georgia Institute of Technology Graphics and Visualization Unit over the Internet. Findings indicate the model best predicts Number of Purchases in a future period, and that Buyer Characteristics are most important to this determination. Further, this model is evolving over Time making Buyer Characteristics predict Number of Purchases better in more recent survey administrations. Buyers clustered into five groups based on level of buying and move through various levels and buy increasing Number of Purchases over time. ^ This is the first large scale research project to investigate the evolution of REC. This implications are significant. Practitioners with casual consumer customers need to deploy a finely tuned REC strategy, understand their buyers, capitalize on the company reputation on the Internet, install an Internet-compatible infrastructure, and web-enable order-entry/inventory/fulliment/shipping applications. Researchers might wish to expand on the Buyer Characteristics of the model and/or explore alternative dependent variables. Further, alternative theories such as Population Ecology or Transaction Cost Economics might further illuminate this new I.S. research domain. ^

Research Note: Biometric Technology Applications and Trends in Hotels

The purpose of this study is to investigate the biometrics technologies adopted by hotels and the perception of hotel managers toward biometric technology applications. A descriptive, cross sectional survey was developed based on extensive review of literature and expert opinions. The population for this survey was property level executive managers in the U.S. hotels. Members of American Hotel and Lodging Association (AHLA) were selected as the target population for this study. The most frequent use of biometric technology is by hotel employees in the form of fingerprint scanning. Cost still seems to be one of the major barriers to adoption of biometric technology applications. The findings of this study showed that there definitely is a future in using biometric technology applications in hotels in the future, however, according to hoteliers; neither guests nor hoteliers are ready for it fully.

The adoption of retail electronic commerce: an empirical investigation

The purpose of this study was to empirically investigate the adoption of retail electronic commerce (REC). REC is a business transaction which takes place over the Internet between a casual consumer and a firm. The consumer has no long-term relationship with the firm, orders a good or service, and pays with a credit card. To date, most REC applications have not been profitable. To build profitable REC applications a better understanding of the system's users is required. The research model hypothesizes that the level of REC buying is dependent upon the Buying Characteristics of Internet Use and Search Experience plus the Channel Characteristics of Beliefs About Internet Vendors and Beliefs About Internet Security. The effect of these factors is modified by Time. Additional research questions ask about the different types of REC buyers, the differences between these groups, and how these groups evolved over time. To answer these research questions I analyzed publically available data collected over a three-year period by the Georgia Institute of Technology Graphics and Visualization Unit over the Internet. Findings indicate the model best predicts Number of Purchases in a future period, and that Buyer Characteristics are most important to this determination. Further, this model is evolving over Time making Buyer Characteristics predict Number of Purchases better in more recent survey administrations. Buyers clustered into five groups based on level of buying and move through various levels and buy increasing Number of Purchases over time. This is the first large scale research project to investigate the evolution of REC. This implications are significant. Practitioners with casual consumer customers need to deploy a finely tuned REC strategy, understand their buyers, capitalize on the company reputation on the Internet, install an Internet-compatible infrastructure, and web-enable order-entry/inventory/fulfillment/ shipping applications. Researchers might wish to expand on the Buyer Characteristics of the model and/or explore alternative dependent variables. Further, alternative theories such as Population Ecology or Transaction Cost Economics might further illuminate this new I.S. research domain.

The relationship between student characteristics, computer literacy,technology acceptance, and distance education student satisfaction

The purpose of this study is to identify the relationship between the characteristics of distance education students, their computer literacy and technology acceptance and distance education course satisfaction. The theoretical framework for this study will apply Rogers and Havelock's Innovation, Diffusion & Utilization theories to distance education. It is hypothesized that technology acceptance and computer competency will influence the student course satisfaction and explain the decision to adopt or reject distance education curriculum and technology. Distance education delivery, Institutional Support, Convenience, Interactivity and five distance education technologies were studied. The data were collected by a survey questionnaire sent to four Florida universities. Three hundred and nineteen and students returned the questionnaire. A factor and regression analysis on three measure of satisfaction revealed significant difference between the three main factors related to the overall satisfaction of distance education students and their adoption of distance education technology as medium of learning. Computer literacy is significantly related to greater overall student satisfaction. However, when competing with other factors such as delivery, support, interactivity, and convenience, computer literacy is not significant. Results indicate that age and status are the only two student characteristics to be significant. Distance education technology acceptance is positively related to higher overall satisfaction. Innovativeness is also positively related to student overall satisfaction. Finally, the technology used relates positively to greater satisfaction levels within the educational experience. Additional research questions were investigated and provided insights into the innovation decision process.