Search results

Internet of Things (IoT) presents new privacy dilemmas. While IoT is becoming more common, a model to understand privacy concerns has not been established. The purpose of this paper is to examine an existing privacy model, the mobile users’ information privacy concerns (MUIPC), in the context of IoT.

A survey was distributed via email to 1,257 undergraduate students enrolled in a Carnegie Master’s level university in the mid-south; 192 students completed the survey, a response rate of 15.3%. SmartPLS, a structural equation modeling software, was used to evaluate the measurement model and to examine the relationships.

All relationships were significant at the 0.05 level indicating that the MUIPC model does appear to apply to IoT.

A convenience sample was used and the response rate was low and, therefore, may not be generalizable to another population.

This research demonstrates the MUIPC is indeed applicable to privacy research within IoT, thus opening another avenue for future research and confirms the influence of information privacy upon intention within the IoT realm.

This paper aims to improve understanding of individuals' awareness and perceptions of computer usage policies (CUPs) and why individuals elect not to read these policies.

MBA students were asked to complete an online survey evaluating their behavioral intention to read CUPs, as well as their performance of this behavior. Factors contributing to the intention to read policies were also examined. The resulting data were analyzed with Smart PLS.

Results suggest that three factors influence individual intention to read CUPs. These factors include attitude, apathy, and social trust. The model explained about 70 percent of individual intention to read CUPs and about 44 percent of the variability in actually reading these policies.

The sample is limited to MBA students from a single university.

Although written policy statements are often considered the cornerstone of computer security, many individuals elect not to read these policies. Thus, other methods of communication must be used.

This paper examines the reasons individuals elect not to read CUPs. Given the importance of these policies as deterrents to information systems misuse and computer crime, understanding why individuals fail to read policies is a critical first step in enhancing user knowledge of computer security.

The term cyberterrorism is being used with increasing frequency today. Since widespread concern with cyberterrorism is relatively new, understanding of the term is somewhat limited. Government officials and experts are often heard claiming that the world is unprepared for cyberterrorism; however, other officials and experts state that cyberterrorism does not pose a threat to anyone. Examines the reasons for these disparate viewpoints and reviews the theoretical and actual forms in which cyberterrorism may occur. Further, proposes the use (and refocusing) of an existing model of computer security to help understand and defend against cyberterrorism.

Although many universities require courses in management information systems for their business majors, little information exists as to what objectives should be included in the course, and the course topics vary greatly across institutions. Differences in course objectives even exist within schools if multiple sections of the course are taught by different faculty. Typically, a significant portion of the class is devoted to database concepts. In many cases, the course requirements include developing a database for a small business. This database project can consume faculty time and resources, especially if student teams choose their own projects and no guidelines exist for faculty reference. In this paper, guidelines for developing a standardized database project that challenges students while freeing up faculty resources are presented. Experiences in dealing with these projects in both face‐to‐face and online classes at one university are detailed.

Partial least squares structural equation modeling (PLS-SEM) has become popular in the information systems (IS) field for modeling structural relationships between latent variables as measured by manifest variables. However, while researchers using PLS-SEM routinely stress the causal-predictive nature of their analyses, the model evaluation assessment relies exclusively on criteria designed to assess the path model's explanatory power. To take full advantage of the purpose of causal prediction in PLS-SEM, it is imperative for researchers to comprehend the efficacy of various quality criteria, such as traditional PLS-SEM criteria, model fit, PLSpredict, cross-validated predictive ability test (CVPAT) and model selection criteria.

A systematic review was conducted to understand empirical studies employing the use of the causal prediction criteria available for PLS-SEM in the database of Industrial Management and Data Systems (IMDS) and Management Information Systems Quarterly (MISQ). Furthermore, this study discusses the details of each of the procedures for the causal prediction criteria available for PLS-SEM, as well as how these criteria should be interpreted. While the focus of the paper is on demystifying the role of causal prediction modeling in PLS-SEM, the overarching aim is to compare the performance of different quality criteria and to select the appropriate causal-predictive model from a cohort of competing models in the IS field.

The study found that the traditional PLS-SEM criteria (goodness of fit (GoF) by Tenenhaus, R2 and Q2) and model fit have difficulty determining the appropriate causal-predictive model. In contrast, PLSpredict, CVPAT and model selection criteria (i.e. Bayesian information criterion (BIC), BIC weight, Geweke–Meese criterion (GM), GM weight, HQ and HQC) were found to outperform the traditional criteria in determining the appropriate causal-predictive model, because these criteria provided both in-sample and out-of-sample predictions in PLS-SEM.

This research substantiates the use of the PLSpredict, CVPAT and the model selection criteria (i.e. BIC, BIC weight, GM, GM weight, HQ and HQC). It provides IS researchers and practitioners with the knowledge they need to properly assess, report on and interpret PLS-SEM results when the goal is only causal prediction, thereby contributing to safeguarding the goal of using PLS-SEM in IS studies.

This study investigates the potential of utilizing mindfulness practices to regulate emotions in libraries. Libraries are emotionally stressful environments characterized by continuous change and uncertainty. Working with the public and with colleagues can lead to emotional strain and exhaustion. Mindfulness offers librarians a means to achieve a degree of emotional control so they do not identify with emotions, allowing them to focus more fully on their work. This study examines the scientific research that has been conducted on mindfulness and the effect it has on emotions. The research is drawn from the fields of psychology and related fields such as medicine. The findings are applied to the library field to examine what the potential implications might be. Psychological studies have shown that mindfulness has the potential to effectively manage emotions in the workplace and in organizational settings. Mindfulness practices help individuals manage emotions by a process of attuning to and dis-identifying with affective content, leaving them free to concentrate on the task at hand. Psychological science has found mindfulness to be useful for managing emotions. These findings have potential implications for libraries. By applying mindfulness to the library setting, this study provides librarians with an effective strategy for regulating emotions and coping with work-related stress.

To provide useful references for manufacturing industry which guide the linkage of business strategies and performance indicators for information security projects.

This study uses balanced scorecard (BSC) framework to set up performance index for information security management in organizations. Moreover, BSC used is to strengthen the linkage between foundational performance indicators and progressive business strategy theme.

The general model of information security management builds the strategy map with 12 strategy themes and 35 key performance indicators are established. The development of strategy map also express how to link strategy themes to key performance indicators.

The investigation of listed manufacturing companies in Taiwan may limit the application elsewhere.

Traditional performance measurement system like return on investment, sales growth is not enough to describe and manage intangible assets. This study based on BSC to measure information security management performance can provide the increasing value from improving measures and management insight in modern business.

This study combines the information security researches and organizational performance studies. The result helps organizations to assess values of information security projects and consider how to link projects performance to business strategies.

Division of motor vehicle (DMV) offices serve a wide swath of Americans in all states and can therefore serve as excellent vehicles to study the quality of public services in the country. However, relatively little attention has been devoted in the academic literature to studying operations in DMV offices, especially as it relates to service quality and productivity. In an attempt to address the same, this paper aims to present the results of a study of DMV offices across the USA through a nationwide survey about vehicle titling and registration services, that received response from 31 of the 50 states and District of Columbia.

The authors use a mixed methods approach – a sequential unequal weight mixed methods approach starting with a quantitative analysis of DMV operational data followed by a qualitative case study approach. The primary data collected for this study were with a nationwide survey of the highest DMV office in each state, conducted through the American Association of Motor Vehicle Administrators. Out of the 50 states, 31 states and District of Columbia responded to the survey. In addition to descriptive statistical analysis performed to glean nationwide findings, Data Envelopment Analysis was used to determine efficiency of operations. Finally, extensive in-person interviews with senior managers of DMV offices in Ohio and Indiana were conducted to get more in-depth information for case studies and identification of best practices.

States exhibit significant variations in labor and capital productivity and based on Data Envelopment Analysis, Texas and Minnesota DMVs are the most efficient in terms of using their labor and capital inputs to maximize the number of transactional services rendered. The authors also find that while operational performance of vehicle titling and registration services is monitored by most DMV offices across the nation, assessment of customer satisfaction received much less attention. Among the states that do well on both are Indiana and Ohio; the case studies presented based on interviews with their officials that also identify best practices.

This research was limited to the USA as are its findings. Additionally, it focuses only on vehicle titling and registration at DMV offices because that represents the bulk of services performed by a DMV and the output is standard across all states. Nonetheless, a future study should be extended to other DMV services.

Given the finding that assessment of customer satisfaction is not widely practiced in DMV offices, DMV officials should address this by putting appropriate systems in place. Additionally, practitioners and state officials can use the findings of this study to develop best practices for their operations and also determine the most appropriate ways to structure the provision of those services that result in enhanced efficiencies and customer satisfaction.

DMV services are among the most widely used services offered by the government in the USA and the overall size and scope of services provided by them across the country is immense. Thus, any improvements in productivity and service quality has significant implications in terms of improving public satisfaction with government services.

To the best of our knowledge, this represents the first nationwide comparative study of DMV offices in the USA that focuses on service quality and analyzes productivity across the states. Additionally, the case study provided at the end of the paper identifies best practices from two states that have received national recognition for service quality which could be adopted by all DMV offices across the USA. The findings also conform/strengthen numerous hypotheses espoused in existing models and theories from service operations literature by providing evidence in their favor.