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Journal of Organizational Computing and Electronic Commerce 24

Editors:Clyde W. Holsapple
Publisher:Taylor & Francis
Standard No:ISSN 1091-9392 (print) 1532-7744 (online)
Links:Table of Contents
  1. JOCEC 2014-01-02 Volume 24 Issue 1
  2. JOCEC 2014-04-03 Volume 24 Issue 2/3
  3. JOCEC 2014-10-02 Volume 24 Issue 4

JOCEC 2014-01-02 Volume 24 Issue 1

Determinants of Success for Online Insurance Web Sites: The Contributions from System Characteristics, Product Complexity, and Trust BIBAFull-Text 1-35
  Wei-Tsong Wang; Chia-Cheng Lu
Few studies have considered the determinants of the success of electronic commerce Web sites from an integrated viewpoint, including the technical, psychological, and product-characteristic perspectives. By expanding DeLone and McLean's information system success model, this study develops a model of the impacts of system quality, information quality, perceived product complexity, trust, and satisfaction on repurchase intention in the context of online insurance Web sites. Data collected from 270 online-insurance-Web site consumers provide support for the model. The results indicate that perceived product complexity, trust, and satisfaction are determinants of repurchase intention. In addition, system quality and information quality significantly affect both perceived product complexity and trust. Furthermore, perceived product complexity is found to be a significant mediator of the indirect effects of system quality and information quality on customer satisfaction, and trust and satisfaction are statistically verified to be significant mediators of the indirect effects of system quality, information quality, and perceived product complexity on repurchase intentions. The research results provide online sellers with significant insights into the development of online systems and product/services that can better fulfill the needs of potential and repeat consumers. The theoretical and practical implications of this work are discussed.
The Influence of Seller, Auctioneer, and Bidder Factors on Trust in Online Auctions BIBAFull-Text 36-57
  Chin-Shan Wu; Fei-Fei Cheng; David C. Yen
A growing body of research promotes the importance of trust in the business-to-consumer e-commerce environment. However, there has been little research on consumer trust in the new frontier of consumer-to-consumer (C2C) online auctions. The current study investigates the factors that influence bidders' trust in online auctions from seller (trust arguments), bidder (disposition to trust), and auctioneer (structural assurance and perceived Web risk) perspectives in order to provide a more comprehensive understanding of trust in the C2C environment. Laboratory experiments (manipulating the trust arguments in "about me" page) and online questionnaire surveys (measuring the subjects' responses regarding structural assurance, perceived risk, disposition to trust, trust, and purchase intention) were conducted to collect necessary data. The results suggest that benevolent sellers significantly influence the trust of bidders. Analysis also finds that structural assurance is the most influential predictor of trust, which significantly influences a buyer's intention to purchase. In addition, disposition to trust is a significant predictor of trusting belief, whereas perceived Web risk does not predict purchase intention.
Effect of Reputation Mechanisms and Ratings Biases on Traders' Behavior in Online Marketplaces BIBAFull-Text 58-73
  Riyaz Sikora; Liangjun You
Rating mechanisms are becoming an essential tool for online shoppers. There have been many reputation mechanisms proposed in the literature that try to mitigate the sometimes adverse effects of strategic behavior of the traders to alter their true reputation scores. At the same time, several studies have shown the presence of bias (often unintentional) in product ratings and their harmful effect on buyers and product sales. To date, there has not been any work done that studies the effect of reputation mechanisms and ratings biases on the behavior of buyers and sellers in an online marketplace. In this article, we use the concept of replicator dynamics to study the evolution of different types of sellers and buyers who use three different reputation mechanisms. We also study the evolution of different types of sellers in the presence of four types of ratings biases. Our results indicate that, over time, buyers gravitate toward using the adaptive model and, in most scenarios, strategic and dishonest sellers are replaced by honest sellers.
Social Media in Organizations: Leveraging Personal and Collective Knowledge Processes BIBAFull-Text 74-93
  Liana Razmerita; Kathrin Kirchner; Thierry Nabeth
By using social media, many companies try to exploit new forms of interaction, collaboration, and knowledge sharing through leveraging the social, collaborative dimension of social software. The traditional collective knowledge management model based on a top-down approach is now opening up new avenues for a bottom-up approach incorporating a more personal knowledge management dimension, which could be synergized into collective knowledge using the social-collaborative dimension of social media. This article addresses the following questions: (1) How can social media support the management of personal and collective knowledge using a synergetic approach? (2) Do the personal and collective dimensions compete with each other, or can they reinforce each other in a more effective manner using social media? Our findings indicate that social media supports both the personal and collective dimensions of knowledge, while integrating a social collaborative dimension. The article introduces a framework that classifies social software into four categories according to the level of interaction and control. With certain tools, individuals are more in control. With other tools, the group is in control, resulting in a higher level of interaction and a diversity of knowledge and mindsets brought together. However, deploying and adopting these new tools in an organizational context is still a challenging task for management, owing to both organizational and individual factors.
Analyzing Massive Data Sets: An Adaptive Fuzzy Neural Approach for Prediction, with a Real Estate Illustration BIBAFull-Text 94-112
  Jian Guan; Donghui Shi; Jozef M. Zurada; Alan S. Levitan
Drawing useful predictions from vast accumulations of data is becoming critical to the success of an enterprise. Organizations' databases grow exponentially from transactions with external stakeholders in addition to their own internal activities. An important organizational computing issue is that, as they grow, the databases become potentially more valuable and also more difficult to analyze. One example is predicting the value of residential real estate based on past comparable sales transactions. This is critical to several important sectors of the US economy including the mortgage finance industry and local governments that collect property taxes. The common methodology for dealing with such property valuation is based on multiple regression, although this methodology has been found to be deficient. Data mining methods have been proposed and tested as an alternative, but the results are very mixed. This article introduces a novel approach for improving predictions using an adaptive, neuro-fuzzy inference model, and illustrates its application to real estate property price prediction through the use of comparable properties. Although neuro-fuzzy-based approaches have been found to be effective for classification and estimation in many fields, there is very little existing work that investigates their potential in a real estate context. In addition, this article addresses several common problems in existing studies, such as small sample size, lack of rigorous data sampling, and poor model validation and testing. Our model is tested with real sales data from the assessment office in a large US city. The results show that the neuro-fuzzy model is superior in all of the test scenarios. The article also discusses and refines a unique technique to defining comparable properties to improve accuracy. Test results show very promising potential for this technique in mass appraisal in real estate and similar contexts when used with the neuro-fuzzy model.

JOCEC 2014-04-03 Volume 24 Issue 2/3

Introduction: Social Computing and Social Networks BIBFull-Text 119-121
  Jinjun Chen; Jianxun Liu
Social Media Around the GLOBE BIBAFull-Text 122-137
  Daniel Schlagwein; Pattarawan Prasarnphanich
Building on the GLOBE study of cultural values, this article explores the impact of societal culture on organizational social media use. The analysis reported in this article is based on data collected from the Fortune Global 500 organizations regarding their use of six different types of external social media. The results of the analysis indicate that societal culture has to be considered an important factor for organizational social media use.
Making the Most of Virtual Expertise in Telemedicine and Telehealth Environment BIBAFull-Text 138-156
  Craig Standing; Raj Gururajan; Susan Standing; Helen Cripps
Virtual expertise is a critical component of telehealth projects and it needs to be effectively managed if telehealth is to deliver on its potential. There are many issues within telehealth that relate to the management of knowledge, and we identify and classify these using a range of papers on the topic. We introduce a virtual expertise platform that provides basic building blocks for effect-leveraging of expertise in this domain. The platform includes management directives and goals, a collaborative culture, an appropriate information and communication technology platform, a knowledge management layer, and a tools or application layer that interact to facilitate knowledge sharing, and ultimately improve patient care. We also emphasize how social media tools can be used as part of the tools layer to improve virtual knowledge sharing before and after telehealth events.
Interactive Mining of Strong Friends from Social Networks and Its Applications in E-Commerce BIBAFull-Text 157-173
  Syed K. Tanbeer; Carson K. Leung; Juan J. Cameron
Social networks are generally made of individuals who are linked by some types of interdependencies such as friendship. Most individuals in social networks have many linkages in terms of friends, connections, and/or followers. Among these linkages, some of them are stronger than others. For instance, some friends may be acquaintances of an individual, whereas others may be friends who care about him or her (e.g., who frequently post on his or her wall). In this study, we integrate data mining with social computing to form a social network mining algorithm, which helps the individual distinguish these strong friends from a large number of friends in a specific portion of the social networks in which he or she is interested. Moreover, our mining algorithm allows the individual to interactively change his or her mining parameters. Furthermore, we discuss applications of our social mining algorithm to organizational computing and e-commerce.
Cloud Requirements for Facilitating Business Collaboration: A Modeling Perspective BIBAFull-Text 174-185
  I. T. Hawryszkiewycz
This paper describes how to design systems that support large scale collaboration between enterprises on the cloud. To do this, the paper proposes an innovative modeling method for large scale collaboration. The modeling method identifies the collaborative spaces in the collaboration and describes ways to support the collaboration in cloud environments, including defining knowledge flows across system boundaries. The modeling focuses on the ability to deploy the cloud to quickly create collaborative environments. Common access to the cloud makes it an enhancer of collaboration, especially across large business networks such as outsourcing or co-design and to support the agility needed in such collaboration. The paper proposes that cloud provides an advantage where it can foster the collaboration needed to maintain sustainable communities and defines the support needed from the cloud for collaboration. This is particularly relevant to smart cities and the greater emphasis on the Internet of things.
The Power of Social Network Construction and Analysis for Knowledge Discovery in the Medical Referral Process BIBAFull-Text 186-214
  Wadhah Almansoori; Omar Addam; Omar Zarour; Mohamad Elzohbi; Abdullah Sarhan; Mehmet Kaya; Jon Rokne; Reda Alhajj
The social network model is powerful enough to provide for the analysis and study of a variety of application domains from daily life, including health care and health informatics. After the widespread appearance of automated tools capable of deriving and analyzing social networks, social network analysis (SNA) and mining in the health care domain has recently received considerable attention for its key role in understanding how various bodies within the health care system form communities and how they are socially connected with each other. This understanding helps enhance the organizational structures and process flows, among others. In this article, we show how SNA techniques can solve issues in the medical referral system in the Canadian health care system and the like, by analyzing the social network of general practitioners (GPs) and specialists (SPs). One of the main targets is to optimize the communication between GPs and SPs with hopes of decreasing the waiting time of patients to be seen by SPs. Various SNA and mining techniques are described and analyzed, backed by reporting some experimental results.
Website Interaction Network BIBAFull-Text 215-235
  Xiangfeng Luo; Huimin Liu; Junyu Xuan
The websites-based social network, as a social media, provides and shares abundant information via organizing users' content and contacts, whereby users' activities in the real world can be imaged to the websites. However, users' content and contacts in real-world social networks cannot be detected easily. Herein, we construct a website interaction network to reflect the online social network, based on mapping relationships among websites, webpages, and attributes of a social event. This network reflects the social association relationships between websites of an event, which can be mapped to the users' relationships in the real-world social network. In this article, we study the structural features of a website interaction network and, then, mapping of these features to the real-world social network. Further, we discuss implications for human behaviors, human relationships, and structure of human society. Experimental results show that the website interaction networks concerning popular social events have power-law scaling in degree distribution and exhibit small-world properties.
Social Network Analysis and Communication in Emergency Response Simulations BIBAFull-Text 236-256
  Milica Stojmenovic; Gitte Lindgaard
In this article, social network analysis (SNA) is applied on two emergency responses, involving chemical, biological, radiological, nuclear, and explosives (CBRNE) simulations. However, SNA has seldom been used in the literature to explain communication breakdowns, leading to the question of "can it"? To examine the applicability of SNA when assessing communication, the SNAs of two CBRNE simulations are compared and the structural differences are related to instances of ineffective communication. Study 1 has two tiers in the response (commanders and first responders) and Study 2 has three tiers, where operations officers are added between the commanders and first responders. A higher percentage of communication breakdowns is found in Study 2, possibly as a result of the additional layer. SNA provides researchers with a convenient representation and summary of team functioning. However, basic SNA does not help researchers distinguish between effective communication and breakdown. Breakdowns are attributed to long multi-hop communications, attributable to larger networks.
A Location Recommender Based on a Hidden Markov Model: Mobile Social Networks BIBAFull-Text 257-270
  Jialing Li; Li Li
With the development of mobile communication technology and location-based services, people can share information with friends through checking in anywhere, at any time. If we can "speculate" when users will next check in, we can make relevant and useful recommendations. Here, we introduce a new check-in-based hidden Markov model to cope with changing circumstances. A certain check-in-based hidden Markov model for each group is obtained first. The model then analyzes temporal check-in intervals of users before suggesting locations. We also discuss optimal parameter settings for the number of hidden states and the corresponding number of user groups. Experiments show that, given observations of a new entrant, the model is able to predict the most probable time period the user will check in next time. It can also recommend a specific user group for the new entrant. Hence, it enables the recommendation of potential locations of interest for the new entrant.

JOCEC 2014-10-02 Volume 24 Issue 4

Determinants of Commitment in an Online Community: Assessing the Antecedents of Weak Ties and Their Impact BIBAFull-Text 271-296
  Lili Liu; Christian Wagner; Huaping Chen
Research argues that participants contribute to online communities because they have developed commitment to that community. Even relatively light commitment -- "weak ties" -- can make an impact on community participation. We hypothesize and empirically verify that users' reading activity is an important factor in creating commitment. In doing so, we support and contextualize the Theory of Weak Ties through the investigation of weak "readership ties." Our research formulates both of these constructs, readership ties and commitment, as part of a larger model that identifies perceived site asset value as an important antecedent for readership ties and, thus, commitment. The empirical investigation draws on survey data from 144 members of the Slashdot community. We find all of our hypotheses confirmed, indicating that all types of site assets (community members, knowledge, and technology) increase perceived site value, and that, in turn, increased perceived site asset value leads to more active usage and higher commitment, thus demonstrating the impact of weak ties.
Computer-Aided Tools in Negotiation: Negotiable Issues, Counterfactual Thinking, and Satisfaction BIBAFull-Text 297-311
  Terence T. Ow; Bonnie S. O'Neill; Charles E. Naquin
Negotiations research has identified both economic and social-psychological outcomes are important for negotiations. Despite the economic advantages of having multiple issues to negotiate, inconsistencies exist between objective economic outcomes and negotiator satisfaction. Although having more negotiable issues yields better objective payoffs, it can result in more thoughts about different possible outcomes. Such counterfactual thoughts about different outcomes can reduce overall satisfaction due to increased cognitive complexity and thoughts about different outcomes. In this study, we explore how information technology can influence negotiator satisfaction and better manage counterfactual thoughts and post-negotiation satisfaction. Results support the prediction that having a computer aid to better manage cognitively complex issues, even a relatively simple one, reduces participants' counterfactual thoughts about better possible outcomes. As a result, the use of some type of technology -- even a simple technology such as a spreadsheet -- may improve overall negotiator satisfaction, while maintaining desirable economic outcomes.
Business-to-Business Electronic Commerce Success: A Supply Network Perspective BIBAFull-Text 312-341
  Morteza Ghobakhloo; Tang Sai Hong; Craig Standing
DeLone and McLean (2004) have advanced an electronic commerce (EC) success model and suggest that it can be extended to investigating EC success in different contexts. However, the EC success model has not been empirically validated in the context of business-to-business (B2B) EC. The purpose of this study is to gain a better understanding of EC value and success within the B2B environment. Accordingly, we introduce an extended version of DeLone and McLean's (2004) EC success model, and test hypotheses regarding the associations between various success dimensions using the data collected from 122 supply chain units. In addition to providing support for most of the hypotheses suggested by DeLone and McLean's (2004) EC success model, our results indicate that other success dimensions, such as EC readiness, must be considered for successful EC in B2B environments. The research findings provide practitioners with clarity on the levers of B2B e-commerce success within the supply chain unit level of analysis. Overall, the study's results contribute to theoretical development in the area of business value creation and EC success, and present a basis for further research in these fields.
Web Adoption and Firm Performance in the Fashion Industry: The Moderating Role of Social and Economic Rational Managerial Perceptions BIBAFull-Text 342-365
  J. M. Hurtado Gonzalez; S. Bruque Cámara; J. L. Galán Gonzalez
This article draws on an integrated perspective of institutional theory and the resource-based view of the firm by studying the causal relationships among Web technology adoption, social and economic rational managerial perceptions, and firm results. It does so in the context of the fashion industry. The article suggests that both resource-based view and institutional factors may better explain firm performance. Isomorphic rationality as institutional forces of firm homogeneity are proposed as determinants of rent potential that complement and extend resource-based explanations of firm success variation and sustainable competitive advantage in the fashion industry.
Shifting Demand: Online Music Piracy, Physical Music Sales, and Digital Music Sales BIBAFull-Text 366-387
  Byungwan Koh; B. P. S. Murthi; Srinivasan Raghunathan
Traditionally, music has been sold to consumers by recording several individual songs/tracks in physical media such as CDs and cassettes. Sales of such physical music have been declining for the past several years. Many academic studies have attributed the decline of physical music sales to online music piracy, yet some other studies have not found evidence to support a negative relationship between online music piracy and physical music sales. Interestingly and importantly, we have observed that while many of the studies that found the negative relationship between online music piracy and physical music sales used data before 2003, other studies that do not find similar results have used post-2003 data. In fact, there was a significant structural change in the music market in 2003. Legal (iTunes-like) online channels for digital music that allow consumers to buy individual tracks became available during that year. This article complements the existing literature by analyzing the impact of online music piracy and physical music sales in the presence of iTunes-like legal channels for digital music using bivariate Granger testing. Our results show that the availability of legal channels for digital music has weakened the negative effect of online music piracy on physical music sales. Moreover, in the presence of legal channels for music distribution, digital music, not online music piracy, substitutes for physical music.
The Medicare Electronic Health Records (EHR) Incentive Program: First-Year Adoption Response from Inpatient Hospitals BIBAFull-Text 388-401
  Rajesh Mirani; Anju Harpalani
This study investigates electronic health records (EHR) adoption among inpatient hospitals in response to the first operational year of the Medicare EHR Incentive Program. Profile analysis of public attestation datasets finds both system adoption rates and implemented functionalities to have been significantly influenced by the incentive program's attributes. Key dates and periods in the program's well-publicized timeline were usually accompanied by spikes in the number of attested systems and/or dips in advanced functionalities. The implication is that hospitals have responded to the program by swiftly implementing EHR systems with capabilities just sufficient to meet program requirements, in order to be able to promptly file attestations and thus claim their incentive payments. The program therefore appears to have yielded mixed results. While it seems to have induced more hospitals to acquire EHR systems, the implemented systems generally possess minimal functionalities, suggesting that adopters have leveraged the program's rules in order to maximize their own short-term gains.