Showing papers in "Journal of the Association for Information Systems in 2011"
TL;DR: A research model suggests that an individual’s privacy concerns form through a cognitive process involving perceived privacy risk, privacy control, and his or her disposition to value privacy, and individuals’ perceptions of institutional privacy assurances are posited to affect the riskcontrol assessment from information disclosure.
Abstract: Organizational information practices can result in a variety of privacy problems that can increase consumers’ concerns for information privacy. To explore the link between individuals and organizations regarding privacy, we study how institutional privacy assurances such as privacy policies and industry self-regulation can contribute to reducing individual privacy concerns. Drawing on Communication Privacy Management (CPM) theory, we develop a research model suggesting that an individual’s privacy concerns form through a cognitive process involving perceived privacy risk, privacy control, and his or her disposition to value privacy. Furthermore, individuals’ perceptions of institutional privacy assurances -namely, perceived effectiveness of privacy policies and perceived effectiveness of industry privacy self-regulation -are posited to affect the riskcontrol assessment from information disclosure, thus, being an essential component of privacy concerns. We empirically tested the research model through a survey that was administered to 823 users of four different types of websites: 1) electronic commerce sites, 2) social networking sites, 3) financial sites, and 4) healthcare sites. The results provide support for the majority of the hypothesized relationships. The study reported here is novel to the extent that existing empirical research has not explored the link between individuals’ privacy perceptions and institutional privacy assurances. We discuss implications for theory and practice and provide suggestions for future research.
518 citations
TL;DR: From the analysis of the survey data, an important route of causality is found, as follows: IT personnel expertise, IT management capabilities, IT infrastructure flexibility, and process-oriented dynamic capabilities, and financial performance are found.
Abstract: Research Article Gimun Kim Konyang University gmkim@konyang.ac.kr Bongsik Shin San Diego State University bshin@mail.sdsu.edu Kyung Kyu Kim Yonsei University kyu.kim@yonsei.ac.kr Ho Geun Lee Yonsei University h.lee@yonsei.ac.kr More and more publications are highlighting the value of IT in affecting business processes. Recognizing firmlevel dynamic capabilities as key to improved firm performance, our work examines and empirically tests the influencing relationships among IT capabilities (IT personnel expertise, IT infrastructure flexibility, and IT management capabilities), process-oriented dynamic capabilities, and financial performance. Processoriented dynamic capabilities are defined as a firm’s ability to change (improve, adapt, or reconfigure) a business process better than the competition in terms of integrating activities, reducing cost, and capitalizing on business intelligence/learning. They encompass a broad category of changes in the firm’s processes, ranging from continual adjustments and improvements to radical one-time alterations. Although the majority of changes may be incremental, a firm’s capacity for timely changes also implies its readiness to execute radical alterations when the need arises. Grounded on the theoretical position, we propose a research model and gather a survey data set through a rigorous process that retains research validity. From the analysis of the survey data, we find an important route of causality, as follows: IT personnel expertise IT management capabilities IT infrastructure flexibility process-oriented dynamic capabilities financial performance. Based on this finding, we discuss the main contributions of our study in terms of the strategic role of IT in enhancing firm performance.
391 citations
TL;DR: Ten validity issues associated with the combination of digital trace data and social network analysis methods are examined, with examples from the IS literature, to provide recommendations for improving the validity of future research.
Abstract: There is an exciting natural match between social network analysis methods and the growth of data sources produced by social interactions via information technologies, from online communities to corporate information systems. Information Systems researchers have not been slow to embrace this combination of method and data. Such systems increasingly provide “digital trace data” that provide new research opportunities. Yet digital trace data are substantively different from the survey and interview data for which network analysis measures and interpretations were originally developed. This paper examines 10 validity issues associated with the combination of digital trace data and social network analysis methods, with examples from the IS literature, to provide recommendations for improving the validity of future research.
279 citations
TL;DR: Two empirical studies that examine the interplay between a consumer’s inherent impulsiveness to buy and website quality show that website quality manifests as an environmental cue that directly influences the likelihood that a consumer will experience an urge to buy impulsively.
254 citations
TL;DR: In this paper, the authors proposed a method to solve the problem of the problem: the one-dimensional graph. But it was shown to be ineffective, not useful, in practice.
Abstract: Research Article
136 citations
TL;DR: In this paper, the authors proposed a method to solve the problem of the problem: the one-dimensional graph. But it was shown to be ineffective, not useful, in practice.
Abstract: Research Article
131 citations
TL;DR: It is asserted that users perceive and respond to information technology artifacts as social partners and form perceptions about their social characteristics, and the results indicate that PDPS acts as an antecedent to these beliefs, while the effects of PPS are largely mediated by PDPS.
Abstract: Research Article Sameh Al-Natour American University of Sharjah salnatour@aus.edu Izak Benbasat University of British Columbia izak.benbasat@sauder.ubc.ca Ron Cenfetelli University of British Columbia ron.cenfetelli@sauder.ubc.ca In recent work, researchers have supplemented traditional IS adoption models with new constructs that capture users’ relational, social, and emotional beliefs. These beliefs have given rise to questions regarding their antecedents and the nature of the user-artifact relationship. This paper sheds light on these questions by asserting that users perceive and respond to information technology (IT) artifacts as social partners and form perceptions about their social characteristics. Subsequently, users’ perceptions of the similarity of these characteristics to their own affect evaluations of these artifacts. Within the context of online shopping and using an automated shopping assistant, our paper draws upon social psychology and human-computer interaction research in developing hypotheses regarding the effects of perceived personality similarity (PPS) and perceived decision process similarity (PDPS) on a number of beliefs (enjoyment, social presence, trust, ease of use, and usefulness). The results indicate that PDPS acts as an antecedent to these beliefs, while the effects of PPS are largely mediated by PDPS. Furthermore, the results reveal that the effects of perceived similarity, in general, exceed those of the effects of the individual assessments of the user’s and the assistant’s personalities and decision processes. These results have important implications for IS design. They highlight the importance of designing artifacts that can be matched to users’ characteristics. They also underscore the importance of considering similarity perceptions rather than solely focusing on perceptions of the IT artifact’s characteristics; a common approach in IS adoption research.
111 citations
108 citations
TL;DR: Based on the analysis of 55 IS applications of cluster analysis, various deficiencies noticed in its use are discussed along with suggestions for future practice and longitudinal trends in the application of this technique are highlighted.
Abstract: Research Article VenuGopal Balijepally Prairie View A&M University vebalijepally@pvamu.edu George Mangalaraj Western Illinois University G-Mangalaraj@wiu.edu Kishen Iyengar University of Colorado at Boulder kishen.iyengar@colorado.edu Cluster analysis is a powerful statistical procedure for extricating natural configurations among the data and the populations. Cluster analysis, with its seemingly limitless power to produce groupings in any dataset, has all the trappings of a super-technique. However, the method produces clusters even in the absence of any natural structure in the data, and has no statistical basis to reject the null hypothesis that there are no natural groupings in the data. Application of cluster analysis, therefore, presupposes sound researcher judgment and responsible analysis and reporting. This paper summarizes the results of a reflective review of the application of cluster analysis in Information Systems (IS) research published in major IS outlets. Based on the analysis of 55 IS applications of cluster analysis, various deficiencies noticed in its use are discussed along with suggestions for future practice. By analyzing the results over two time periods, longitudinal trends in the application of this technique are highlighted.
97 citations
93 citations
TL;DR: In this article, the authors proposed a method to solve the problem of the problem: the one-dimensional graph. But it was shown to be ineffective, not useful, in practice.
Abstract: Research Article
TL;DR: Research Article Felix Müller-Wienbergen University of Münster felix.mueller-wenerbergen@ercis.uni-muenster.de
Abstract: Research Article Felix Müller-Wienbergen University of Münster felix.mueller-wienbergen@ercis.uni-muenster.de
TL;DR: Li et al. as discussed by the authors conducted a survey study on SMEs within the United States, and constructed an innovation adoption decision factors classification framework that classifies innovation decision factors into three dimensions: decision entity factors, decision object factors, and context factors.
Abstract: Research Article Xiaolin Li Towson University xli@towson.edu Marvin D. Troutt Kent State University mtroutt@kent.edu Alan Brandyberry Kent State University abrandyb@kent.edu Tuo Wang Kent State University twang3@kent.edu Although more and more small and medium-sized enterprises (SMEs) use the Internet for business purposes, few of them have adopted the Internet as an online direct sales channel (ODSC). Among those that do use the ODSC, some end up abandoning it after adoption. This study explores a few critical factors underlying the initial adoption and continued use of online direct sales channels among SMEs. Synthesizing existing works, we construct an innovation adoption decision factors classification framework that classifies innovation decision factors into three dimensions: decision entity factors, decision object factors, and context factors. We then operationalize these factors in the context of SMEs’ initial adoption and post-adoption continued use of online direct sales channels. We conduct a survey study on SMEs within the United States. The results demonstrate that an SME’s initial adoption and post-adoption continued use of an ODSC involve different sets of decision factors. Furthermore, results demonstrate a learning effect within adopting firms that implies they perceive the relative advantage of ODSC differently in comparison to pre-adopters.
TL;DR: In this article, the authors present a special issue of their book, this article : "The Future of Health.special issues.special issue.1]... ].
Abstract: Special Issue
TL;DR: Xiaojun Zhang Hong Kong University of Science and Technology is the first in the world to award a post-graduate degree in machine learning and artificial intelligence to a female student.
Abstract: Collaborative technologies are widely used to enable teams to function effectively in today's competitive business environment. However, prior research has been inconclusive regarding the impacts of collaborative technologies on team performance. To address the inconsistencies in prior work, this paper seeks to understand the mediational mechanisms that transmit the effect of collaborative technologies on team performance. Specifically, we theorize that there is a relationship between design features and knowledge contextualization. We further theorize relationships between knowledge contextualization and a team's capability for collaboration, specifically examining collaboration know-how and absorptive capacity, both of which are expected to influence team performance. We conduct a field study including 190 software project teams from a large organization in China. The results support our theoretical model and demonstrate that design features have an impact on performance outcomes, mediated by collaboration know-how and absorptive capacity.
TL;DR: Findings support the theoretical importance of including sacrifice and service outcome (parallel with s ervice quality) as a ntecedents of online customer loyalty.
Abstract: Customer loyalty is a key d river o f financial p erformance f or o nline firms. The e ffect o f service q uality o n customer loyalty h as b een well es tablished. Y et, there is a p aucity o f r esearch that has s tudied the c ost o f obtaining s ervice quality d uring t he s ervice process a nd t he s ervice outcome i nfluenced by s uch cost. We extend p revious re search a nd p ropose t he 3S Customer Loyalty M odel b y integrating s acrifice and s ervice outcome a s a dditional i mportant service d imensions t ogether with service q uality when p redicting o nline customer loyalty, and examining how their influences on loyalty vary across customers with different degrees of product k nowledge. Further, we t heorize t hat service quality a nd sacrifice -- as service p rocess d imensions influence s ervice o utcome, and w e theorize h ow “ live help” technology improves customer p erceptions o f service q uality and s acrifice. T he e mpirical r esults indicate that 1 ) c ustomer loyalty i ncreases w ith h igher perceived service quality, lower perceived sacrifice, and better perceived service outcome, 2) service quality and s acrifice i nfluence s ervice o utcome, 3 ) c ustomer p roduct k nowledge n egatively moderates the relationship b etween s ervice q uality a nd o nline c ustomer l oyalty and p ositively moderates t he relationship between s acrifice a nd customer loyalty, and 4 ) live h elp technology en hances service q uality a nd r educes sacrifice. These findings support the theoretical importance of including sacrifice and service outcome (parallel with s ervice quality) as a ntecedents of online customer loyalty. O ur s tudy a lso a dvances t he t heoretical understanding o f what service p rocess c onsists of and how t he s ervice p rocess (i.e. s ervice q uality and sacrifice) influences service outcome.
TL;DR: A case analysis of a prototype health IT application to be shared between the United States Social Security Administration and Beth Israel Deaconess Medical Center found that business, socio-organizational, and technical dynamics were operative during the planning and execution of the prototype.
Abstract: Special Issue Recent developments in health information technology (health IT) for health information exchange suggest that successful public-private collaborations should devote more attention to understanding the dynamics of collaboration. In the context of health information sharing for disability determination, this case study examines early instances of public-private interorganizational sharing of health information. The theoretical focus of the paper is on the construction of blended value propositions and their role in collaboration for health information exchange. For this purpose, we performed a case analysis of a prototype health IT application to be shared between the United States Social Security Administration and Beth Israel Deaconess Medical Center. The case analysis found that business, socio-organizational, and technical dynamics were operative during the planning and execution of the prototype. From a theoretical perspective, the case study provides insight into blended value propositions in terms of understanding and potentially predicting the success of newly established Health Information Exchanges (HIEs). The findings have implications for further development of collaboration value propositions and their evolution over the course of IT deployments for health information exchange.
TL;DR: This research examines the impacts of the assimilation and use of IT on the financial performance of hospitals and finds that the IT applications architecture longevity has a more significant effect on financial performance.
Abstract: This research examines the impacts of the assimilation and use of IT on the financial performance of hospitals We identify two dimensions of IT assimilation and use They are the IT applications architecture spread, which is the adoption of a broad array of IT solutions, and IT applications architecture longevity, which is the length of experience with use of specific IT solutions We examine the extent to which these dimensions of assimilation within the business and clinical work processes impact hospital performance Compared with the effects of IT applications architecture spread, we find that the IT applications architecture longevity has a more significant effect on financial performance In addition, the effects of assimilation manifest differently across the business and clinical process domains Our results enhance understanding about the manner in which the assimilation and use of IT contributes to the financial performance of hospitals
TL;DR: In this paper, the authors present a special issue of their book, this paper : "The Future of Health.special issues.special issue.1]... ].
Abstract: Special Issue
TL;DR: In this article, the authors proposed a diffusion-based recommendation framework on Twitter during the early outbreak of H1N1 Flu, which selects a small subset as recommended emergency news feeds for regular users.
Abstract: Micro-blogging is increasingly evolving from a daily chatting tool into a critical platform for individuals and organizations to seek and share real-time news updates during emergencies. However, seeking and extracting useful information from micro-blogging sites poses significant challenges due to the volume of the traffic and the presence of a large body of irrelevant personal messages and spam. In this paper, we propose a novel recommendation framework to overcome this problem. By analyzing information diffusion patterns among a large set of micro-blogs that play the role of emergency news providers, our approach selects a small subset as recommended emergency news feeds for regular users. We evaluate our diffusion-based recommendation framework on Twitter during the early outbreak of H1N1 Flu. The evaluation results show that our method results in more balanced and comprehensive recommendations compared to benchmark approaches.
TL;DR: “” � £1,000,000”
Abstract:
TL;DR: Special Issue Mark Christopher Shaw De Montfort University explores the "politics of time" in the age of social media and the role that technology has played in shaping public opinion.
Abstract: Special Issue Mark Christopher Shaw De Montfort University
TL;DR: The protocol analysis study shows that DQ tags are associated with increased cognitive processing in the earlier phases of decision making, which delays generation of decision alternatives, and can be explained by understanding the impact of DQtags on decision process using concurrent protocol analysis, which involves participants verbalizing thoughts while making a decision.
Abstract: It has been proposed that metadata describing data quality (DQ), termed DQ tags, be made available in situations where decision makers are unfamiliar with the data context, for example, in data warehouses. However, there have been conflicting reports as to the impact of such DQ tags on decision-making outcomes. Early studies did not explicitly consider the usability and semantics of the DQ tag designs used experimentally or the impact of such tags on decision process, except in suggestions for future research. This study addresses these issues, focusing on the design of usable DQ tags whose semantics are explicitly specified and exploring the impact of such DQ tags on decision outcomes and process. We use the information quality framework InfoQual, the interaction design technique of contextual inquiry, and cognitive process tracing to address DQ tag semantics, usability, and impact on decision process, respectively. In distinct contrast to earlier laboratory experiments, there was no evidence that the preferred decision choice changed with DQ tags, but decision time was significantly increased and there were indications of reduced consensus. These results can be explained by understanding the impact of DQ tags on decision process using concurrent protocol analysis, which involves participants verbalizing thoughts while making a decision. The protocol analysis study shows that DQ tags are associated with increased cognitive processing in the earlier phases of decision making, which delays generation of decision alternatives.
TL;DR: In this article, the authors show that CB-SEM can provide deeper insights into a phenomenon, allowing us to build theories based on quantitative data, rather than test theory, which is traditionally viewed as a method to test theory rather than build it.
Abstract: Covariance-based structural equation modeling (CB-SEM) is an increasingly popular technique for analyzing quantitative data in Information Systems research. As such, it is traditionally viewed as a method to test theory, rather than build it. However, many of the theoretical models tested with this technique in IS research show significant differences between the model and the data. This paper shows that as part of the pursuit of model fit, researchers using CB-SEM can provide deeper insights into a phenomenon, allowing us to build theories based on quantitative data.
TL;DR: It is argued that this type of research holds the promise of bringing fresh insights into the study of human behavior toward information and communication technologies, and thus, helping advance the field of information systems through a promising path that has rarely been taken before.
Abstract: Evolved information processing traits are defined as mental traits that have been evolved by our species in response to evolutionary pressures and that are associated with the processing of information. Evolutionary psychologists and human evolution researchers have long realized that theorizing about evolved mental traits is very difficult to do in ways that lead to valid testable predictions. Quite often that theorizing leads to what are known as Panglossian (or naive) explanations, which may at first glance be seen as valid evolutionary explanations of observable traits, but end up proving to be wrong and misleading. We propose four metatheoretical principles to guide future research on evolved information processing traits and their effects on technology-mediated task performance, and help researchers avoid Panglossian explanations. We argue that this type of research holds the promise of bringing fresh insights into the study of human behavior toward information and communication technologies, and thus, helping advance the field of information systems through a promising path that has rarely been taken before. We derive the four principles from mathematical formulations developed based on two of the most fundamental conceptual tools employed in population genetics and mathematical modeling of evolutionary processes: Fisher’s Fundamental Theorem of Natural Selection and the Price Equation. We provide an illustration of the application of the principles through an empirical study of a technology-mediated learning task. The analysis was conducted using WarpPLS 1.0. The study provides support for a puzzling phenomenon, known as flashbulb memorization, the context of webmediated learning.
TL;DR: This study proposes a theory of diagrammatic attention management to contribute to the exploration of diagram effectiveness, and demonstrates that the type of diagram most commonly used to represent conceptual models is less effective than three other alternatives for validating the models’ cardinalities.
Abstract: Diagrams are frequently used to document various components of information systems, from the procedures established for user-system interaction, to the structure of the database at the system’s core. Past research has revealed that diagrams are not always used as effectively as their creators intend. This study proposes a theory of diagrammatic attention management to contribute to the exploration of diagram effectiveness. Based upon diagrammatic attention management, this study demonstrates that the type of diagram most commonly used to represent conceptual models is less effective than three other alternatives for validating the models’ cardinalities. Most conceptual models are documented using entity-relationship diagrams that include a full transaction cycle or module on a single page, i.e., an aggregate diagrammatic format. Participants in this study using three alternative representations (disaggregate diagrammatic, aggregate sentential, and disaggregate sentential) outperformed users of the aggregate diagrammatic format for cardinality validation. Results suggest that to facilitate effective use of aggregate diagrams, users need a mechanism by which to direct their attention while using the diagrams. If such an attention direction mechanism is not inherent in a diagram, it may need to be applied as an external tool, or the diagram may need to be disaggregated to facilitate use.