A systems approach to describing the process of individual adoption of IT innovations

Research on the adoption of innovations by individuals has been criticized for focusing on various factors that lead to the adoption or rejection of an innovation while ignoring important aspects of the dynamic process that takes place. Theoretical process-based models hypothesize that individuals go through consecutive stages of information gathering and decision making but do not clearly explain the mechanisms that cause an individual to leave one stage and enter the next one. Research on the dynamics of the adoption process have lacked a structurally formal and quantitative description of the process. ^ This dissertation addresses the adoption process of technological innovations from a Systems Theory perspective and assumes that individuals roam through different, not necessarily consecutive, states, determined by the levels of quantifiable state variables. It is proposed that different levels of these state variables determine the state in which potential adopters are. Various events that alter the levels of these variables can cause individuals to migrate into different states. ^ It was believed that Systems Theory could provide the required infrastructure to model the innovation adoption process, particularly applied to information technologies, in a formal, structured fashion. This dissertation assumed that an individual progressing through an adoption process could be considered a system, where the occurrence of different events affect the system's overall behavior and ultimately the adoption outcome. The research effort aimed at identifying the various states of such system and the significant events that could lead the system from one state to another. By mapping these attributes onto an “innovation adoption state space” the adoption process could be fully modeled and used to assess the status, history, and possible outcomes of a specific adoption process. ^ A group of Executive MBA students were observed as they adopted Internet-based technological innovations. The data collected were used to identify clusters in the values of the state variables and consequently define significant system states. Additionally, events were identified across the student sample that systematically moved the system from one state to another. The compilation of identified states and change-related events enabled the definition of an innovation adoption state-space model. ^

Earnings management using estimates and the timing of adoption of accounting standards: An empirical examination of pensions

This study investigates the relationship between adoption timing of Statement of Financial Accounting Standards 87 and earnings management after adoption. Earnings management, defined consistent with Schipper (1989), is tested through hypotheses using (1) a portfolio approach and (2) pension rates. One Hypothesis uses a Modified Jones (1991) Model as a proxy for discretionary accruals and the other uses pension rate estimates.^ Statistically significant relationships are found between adoption timing and (1) discretionary accruals and (2) estimated rate-of-return (ROR) on pension plan assets. Early adopting firms tend to have lower discretionary accruals after adoption than on-time adopters. They also tend to use higher ROR estimates which are not supported by higher actual returns. Thus, while early adopters may be using ROR to manage income, this tends to not result in higher discretionary accruals. ^

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. ^

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.

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. ^

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.

Four essays of environmental risk-mitigation

Expected damages of environmental risks depend both on their intensities and probabilities. There is very little control over probabilities of climate related disasters such as hurricanes. Therefore, researchers of social science are interested identifying preparation and mitigation measures that build human resilience to disasters and avoid serious loss. Conversely, environmental degradation, which is a process through which the natural environment is compromised in some way, has been accelerated by human activities. As scientists are finding effective ways on how to prevent and reduce pollution, the society often fails to adopt these effective preventive methods. Researchers of psychological and contextual characterization offer specific lessons for policy interventions that encourage human efforts to reduce pollution. This dissertation addresses four discussions of effective policy regimes encouraging pro-environmental preference in consumption and production, and promoting risk mitigation behavior in the face of natural hazards. The first essay describes how the speed of adoption of environment friendly technologies is driven largely by consumers' preferences and their learning dynamics rather than producers' choice. The second essay is an empirical analysis of a choice experiment to understand preferences for energy efficient investments. The empirical analysis suggests that subjects tend to increase energy efficient investment when they pay a pollution tax proportional to the total expenditure on energy consumption. However, investments in energy efficiency seem to be crowded out when subjects have the option to buy health insurance to cover pollution related health risks. In context of hurricane risk mitigation and in evidence of recently adopted My Safe Florida Home (MSFH) program by the State of Florida, the third essay shows that households with home insurance, prior experience with damages, and with a higher sense of vulnerability to be affected by hurricanes are more likely to allow home inspection to seek mitigation information. The fourth essay evaluates the impact of utility disruption on household well being based on the responses of a household-level phone survey in the wake of hurricane Wilma. Findings highlight the need for significant investment to enhance the capacity of rapid utility restoration after a hurricane event in the context of South Florida.

Four Essays of Environmental Risk-Mitigation

Expected damages of environmental risks depend both on their intensities and probabilities. There is very little control over probabilities of climate related disasters such as hurricanes. Therefore, researchers of social science are interested identifying preparation and mitigation measures that build human resilience to disasters and avoid serious loss. Conversely, environmental degradation, which is a process through which the natural environment is compromised in some way, has been accelerated by human activities. As scientists are finding effective ways on how to prevent and reduce pollution, the society often fails to adopt these effective preventive methods. Researchers of psychological and contextual characterization offer specific lessons for policy interventions that encourage human efforts to reduce pollution. This dissertation addresses four discussions of effective policy regimes encouraging pro-environmental preference in consumption and production, and promoting risk mitigation behavior in the face of natural hazards. The first essay describes how the speed of adoption of environment friendly technologies is driven largely by consumers’ preferences and their learning dynamics rather than producers’ choice. The second essay is an empirical analysis of a choice experiment to understand preferences for energy efficient investments. The empirical analysis suggests that subjects tend to increase energy efficient investment when they pay a pollution tax proportional to the total expenditure on energy consumption. However, investments in energy efficiency seem to be crowded out when subjects have the option to buy health insurance to cover pollution related health risks. In context of hurricane risk mitigation and in evidence of recently adopted My Safe Florida Home (MSFH) program by the State of Florida, the third essay shows that households with home insurance, prior experience with damages, and with a higher sense of vulnerability to be affected by hurricanes are more likely to allow home inspection to seek mitigation information. The fourth essay evaluates the impact of utility disruption on household well being based on the responses of a household-level phone survey in the wake of hurricane Wilma. Findings highlight the need for significant investment to enhance the capacity of rapid utility restoration after a hurricane event in the context of South Florida.