Predicting open IOS adoption in SMEs: An integrated SEM-neural network approach

This research examines the predictors of open interorganizational systems (IOS) adoption by using RosettaNet as a case study. The model used in this research derived its theoretical supports from literature related to interorganizational relationships and knowledge management studies. A sequential, multi-method approach integrating both structural equation modeling (SEM) and neural network analysis was employed in this research. Data was collected from 136 small and medium sized enterprises (SME). Our result showed that interorganizational relationships such as communication, collaboration and information sharing play an important role in SMEs’ RosettaNet adoption decisions. Knowledge management practices such as knowledge application, knowledge acquisition and knowledge dissemination also influenced SMEs’ decision to adopt RosettaNet. The findings are useful for decision makers to understand how they can improve the adoption of RosettaNet in their organizations. Unlike previous studies, this research provided additional insights into what influence the adoption of RosettaNet by examining variables beyond the traditional technological attributes which have been studied quite extensively. By integrating SEM with artificial intelligence techniques such as neural network, this study also examined the non-linear and non-compensatory relationships involved in the adoption of RosettaNet.     

Technology adoption in employee recruitment: The case of social media in Central and Eastern Europe

Social technologies are increasingly used in several organizational functions, including human resource management. The focus of this study is on social media adoption in employee recruitment and selection in Central and Eastern Europe (CEE). The theoretical lens used in this study is the Unified Theory of Acceptance and Use of Technology (UTAUT), extended to include the impact of the recruiters' managerial position and educational level on technology adoption. Results obtained from partial least squares path modeling, using cross-sectional data collected from 224 recruiters, showed that the core hypotheses of the UTAUT were supported, namely the positive impact of performance expectancy, effort expectancy and social influence on behavioral intention, as well as the positive impact of facilitating conditions and behavioral intention on usage behavior. As expected, the recruiters' characteristics triggered many interaction effects, but none of them impacted facilitating conditions. Managerial implications are discussed and future research suggestions are provided.     

Understanding the successful adoption and use of IS/IT in SMEs: an explanation from Portuguese manufacturing industries

Abstract. The objectives of the research were to identify factors enabling or inhibiting the adoption and use of information systems and technology (IS/IT) in Portuguese manufacturing small and medium‐sized enterprises (SMEs) and understand how these factors interrelate in determining relative success in the adoption and use of IS/IT. This research elicited factors from previous quantitative and qualitative research, which had been shown to influence IS/IT adoption in SMEs in other contexts. A strategic change framework was used to structure the factors and ensure that comprehensive evidence about their nature and effects could be obtained in the empirical research. Further factors were identified by initial fieldwork, before carrying out 12 in‐depth case studies, across a range of situations – different industries, different levels of adoption and a range of degrees of success in IS/IT use. The pattern that emerged from the analysis of the data shows that certain factor combinations and relationships appear to determine the relative degrees of IS/IT success across the firms. This pattern can also be explained by interpreting the roles and relationships of the key actors involved in the process of IS/IT adoption and use. Top management perspectives and attitudes towards IS/IT adoption and use play an important role in the development of internal IS/IT competencies and provide an important contribution to the development of a context that enables IS/IT success.     

The reciprocal effects of social network site use and the disposition for self-disclosure: A longitudinal study

Since the advent of social network sites (SNSs), scholars have critically discussed the psychological and societal implication of online self-disclosure. Does Facebook change our willingness to disclose personal information? The present study proposes that the use of SNSs and the psychological disposition for self-disclosure interact reciprocally: Individuals with a stronger disposition show a higher tendency to use SNSs (selection effect). At the same time, frequent SNS use increases the wish to self-disclose online, because self-disclosing behaviors are reinforced through social capital within the SNS environment (socialization effect). In a longitudinal panel study, 488 users of SNSs were surveyed twice in a 6 months interval. Data were analyzed using structure equation modeling. The proposed reciprocal effects of SNS activities and self-disclosure were supported by the data: The disposition for online self-disclosure had a positive longitudinal effect on SNS use which in turn positively influenced the disposition for online self-disclosure. Both effects were moderated by the amount of social capital users received as a consequence of their SNS use.     

Forecasting managerial turnover through e-mail based social network analysis

In this study we propose a method based on e-mail social network analysis to compare the communication behavior of managers who voluntarily quit their job and managers who decide to stay. Collecting 18 months of e-mail, we analyzed the communication behavior of 866 managers, out of which 111 left a large global service company. We compared differences in communication patterns by computing social network metrics, such as betweenness and closeness centrality, and content analysis indicators, such as emotionality and complexity of the language used. To study the emergence of managers’ disengagement, we made a distinction based on the period of e-mail data examined. We observed communications during months 5 and 4 before managers left, and found significant variations in both their network structure and use of language. Results indicate that on average managers who quit had lower closeness centrality and less engaged conversations. In addition, managers who chose to quit tended to shift their communication behavior starting from 5 months before leaving, by increasing their degree and closeness centrality, the complexity of their language, as well as their oscillations in betweenness centrality and the number of “nudges” they need to send to peers before getting an answer.     

SOS on SNS: Adolescent distress on social network sites

Psychological distress and experiences of peer victimization and social rejection are common among adolescents. Nevertheless, the growing popularity of online Social Network Sites (SNS) among adolescents offers an unprecedented opportunity for early detection of adolescents' distress. This study examined the scope of, and the individual differences that may be associated with, distress sharing on SNS. A total of 413 adolescents (mean age = 15.42, 53.8% girls) completed three questionnaires assessing (a) social media usage, (b) distress sharing on SNS, and (c) feelings of social rejection. More than 15% of the sample shared personal distress and searched for help on SNS. Distress sharing did not differ between genders. Social rejection predicted distress sharing on SNS. Notably, social rejection and distress sharing were only associated among individuals with high social media use scores. Implications are discussed for early identification of adolescents' distress.     

The adoption of eCommerce communications and applications technologies in small businesses in New Zealand

This research investigates the impact of 10 factors, extended from the technological innovation literature, on the adoption of different eCommerce communications and applications technologies (EC) in small businesses (SMEs) in New Zealand (NZ). The research results showed that the CEO’s innovativeness was the only determinant of external-email adoption. CEO’s involvement was found to be the only determinant of Intranet adoption. Relative advantage and competition were found to influence Extranet/VPN adoption significantly and positively. However, support from technology vendors appeared to violate its hypothesised effect on Extranet/VPN adoption. Regression analysis found that pressure from suppliers was the only determinant of Internet-EDI adoption. The adoption of Web sites was influenced by the information intensity of products and the CEO’s innovativeness. The significant factors suggested the uniqueness of the adoption phenomenon in SMEs in NZ. However, the factors that appeared to be significant and the ones that appeared to be insignificant factors and the implications arising from these factors led to a conclusion which suggested the weakness of the EC adoption phenomenon in SMEs in NZ. The research discusses theoretical implications emerging from the research factors and portrays a path for future research.     

Social network site use,mobile personal talk and social capital among teenagers

Social network sites (SNSs) and mobile phones are becoming increasingly important in teenagers’ lives. Using data collected from a nationally representative survey (N = 800), this study explores the variation of social capital by SNS adoption, different SNS activities, and mobile personal talk among teenagers. The results indicate that SNS adoption and mobile personal talk can not only enhance teenagers’ close ties with friends, but also jointly promote teenagers’ civic engagement. Among SNS users, mobile personal talk also increase teens’ network capital. Different SNS activities such as commenting on friend’s Facebook pictures and joining Facebook groups have different relationships with social capital, and such relationships are moderated by mobile personal talk.     

BSN: An automatic generation algorithm of social network data

In recent years, there has been considerable interest in the analysis of social network data. In this paper, we propose a novel automatic generation algorithm of social network data - the Biclustering Algorithm for Social Network Data algorithm. The algorithm introduces biclustering to social network analysis for automatic identification of associations among a group of actors and entities. The algorithm is different from existing ones in that it employs a combination of min-max and pattern searching procedures to construct hierarchical biclusters and discover the relationships among these actors, in order to easily interpret social network data. The algorithm is not subject to convexity limitations, and does not need to use derivatives information.     

Individuals’ personal network characteristics and patterns of Facebook use: A social network approach

Using the theoretical framework of ego-centric networks, this study examines the associations between the characteristics of both Facebook-specific and pre-existing personal networks and patterns of Facebook use. With data from an ego-network survey of college students, the study discovered that various dimensions of Facebook-specific network characteristics, such as multiplexity, proximity, density, and heterogeneity in race, were positively associated with usage patterns, including time spent on Facebook, posting messages, posting photos, and lurking. In contrast, network characteristics of pre-existing relationships, such as density and heterogeneity in race, were negatively associated with Facebook usage patterns. Theoretical implications and limitations were discussed.     

Promoting social network awareness: A social network monitoring system

To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system – the KIWI system – that enables users to register their interactions and visualize their social networks. The system was implemented in a distributed research community and the results have shown that KIWI facilitates collecting information about social interactions. Furthermore, the visualization of the social networks, given as feedback, appeared to have a positive impact on the group, augmenting their social network awareness.     

神经网络算法在CRM中的应用

神经网络算法能通过对网络的训练,使客户关系管理系统中客户行为做出预测,便于企业更好为客户服务,改善客户关系,挽留客户.本文就神经网络算法的CRM应用做了相关的探讨.     

Social network sites influence recovery from social exclusion: Individual differences in social anxiety

Social network sites (SNSs) have been found to be closely associated with responses to social exclusion and to impact people with high or low levels of social anxiety in different ways. Our study tested whether social anxiety, an individual difference variable, affected the association between SNSs and responses to social exclusion. A Cyberball game was conducted to create social exclusion, followed by a waiting period during which participants were observed to see whether they would choose to use SNSs. Afterwards, recovery from participants' negative responses to exclusion was measured. Results showed that using SNSs benefited the highly socially anxious (HSA) group in terms of recovering from disconnection and feeling a sense of meaningful existence more than the low socially anxious (LSA) group. However, recovery from disconnection was lower for LSA individuals who used SNSs than those who did not use SNSs. Our research suggests that SNSs benefited HSA individuals after social exclusion, but hindered the recovery of LSA individuals.     

The impact of self-selected identity on productive or perverse social capital in social network sites

Social network sites can provide a person with the freedom to represent themselves in various ways, thus exhibiting multiple variations of their identity. Research states that an individual’s identity is self-monitored depending on the contextual situation that they are in. The type of social capital that one derives from social network sites can be impacted by this self-monitoring ability. Current research has addressed how productive social capital can be gained in social network sites. However, limited research has addressed the issue of perverse social capital, especially in social network sites. We argue that social network sites are a particularly unique environment that can affect an individual’s representation of their identity, thus increasing the likelihood of producing perverse social capital. We examine how technology affects an individual’s selected self-identity, as measured through their self-monitoring ability, and how this altered behavior leads to productive or perverse social capital in social network sites.     

A motives framework of social media website use: A survey of young Americans

Social media is increasingly important in daily life and is an especially important social interaction mechanism for young people. Although research has been conducted evaluating user types based on motives for using social media, no such framework has been extended to social media websites. We extend previous research by evaluating the underlying structure of social media website usage motivations using a 13 item survey and evaluations from 19 different social media websites administered to 1686 young Americans. Using a multidimensional scaling approach, we uncover 2 major motive dimensions underlying social media website use: fun-related and content-specific. Based on the derived dimensions, we generate a graphical “quadrant” system for classifying social media websites and depict all 19 social media sites based on their quadrant. We propose that our quadrant system can be used by other researchers to further refine understanding of social media website usage motives.     

社交网络中热点话题深度挖掘方法及实验测试

互联网大数据时代,社交网络数据交互具有实时性、社会性、复杂性。多元架构数据信息中会存在热点话题数据。传统社交网络热点话题挖掘方法存在热点词条检索速度慢、话题词条层浅、断层数据无法挖掘等一系列问题,如何将社交网络中的热点话题数据进行挖掘,针对这一问题提出大数据信息词条特征比对提取方法,对社交网络中的大数据数据信息词条进行特征显化处理,采用饼图对比方式对特征化词条数据进行网络互交频率展现,采用多维数据获取法,解决社交网络热点话题挖掘中出现的数据阻滞现象,满足社交网络中热点话题深度挖掘的要求。通过仿真实验对提出方法进行效率、准确度、速度测试,实验结果表明,提出方法对社交网络中的热点话题挖掘快捷、高效、实用性强。     

Less effortful thinking leads to more social networking? The associations between the use of social network sites and personality traits

Social network sites (SNS) have become an important social milieu that enables interpersonal communication by allowing users to share and create information. This study explored the associations between SNS use and personality traits, i.e., need for cognition (NFC) and information and communication technology (ICT) innovativeness. The findings showed that the SNS use had a negative association with NFC and a positive association with ICT innovativeness. Specifically, people who were more likely to engage in effortful thinking used SNS less often, and those who were high in ICT innovativeness used SNS more often. Meanwhile, those who spent more time on SNS were more likely to be multitaskers. Additionally, those who spent more time on SNS also spent more Internet time in general, more online time for study/work and more time in surfing the Web with no specific purpose. This study, which could be a first look at the link between social networking and our thinking, provides evidence for the associations between social media use and personality traits.     

Factors mediating disclosure in social network sites

In this paper, we explore how privacy settings and privacy policy consumption (reading the privacy policy) affect the relationship between privacy attitudes and disclosure behaviors. We present results from a survey completed by 122 users of Facebook regarding their information disclosure practices and their attitudes about privacy. Based on our data, we develop and evaluate a model for understanding factors that affect how privacy attitudes influence disclosure and discuss implications for social network sites. Our analysis shows that the relationship between privacy attitudes and certain types of disclosures (those furthering contact) are controlled by privacy policy consumption and privacy behaviors. This provides evidence that social network sites could help mitigate concerns about disclosure by providing transparent privacy policies and privacy controls.     

A model of a trust-based recommendation system on a social network

In this paper, we present a model of a trust-based recommendation system on a social network. The idea of the model is that agents use their social network to reach information and their trust relationships to filter it. We investigate how the dynamics of trust among agents affect the performance of the system by comparing it to a frequency-based recommendation system. Furthermore, we identify the impact of network density, preference heterogeneity among agents, and knowledge sparseness to be crucial factors for the performance of the system. The system self-organises in a state with performance near to the optimum; the performance on the global level is an emergent property of the system, achieved without explicit coordination from the local interactions of agents.     

User-switching behavior in social network sites: A model perspective with drill-down analyses

Social network sites (SNSs) are considered the most representative and influential Web 2.0 applications. Users frequently switch between SNSs and user devices because of the intense SNS market competition and the increasing mobile-device user base. However, the switching behavior of SNS users is yet to be explored to gain new knowledge and practical suggestions. This study uses a higher level research model and lower level switching pattern drill-down analysis to understand the actual switching behavior of SNS users. Users of major SNSs filled out an online questionnaire, which yielded 343 valid samples. The partial least square (PLS) results of the proposed research model show that both service quality and switching cost indirectly influence the switching intention of users through the satisfaction and switching barriers, respectively. Convenience and peer pressure are the top reasons for switching SNS platforms, whereas mobile capabilities and real-time access are the top motivations for switching to mobile SNSs. Six managerial implications are derived from the research model and the switching pattern analysis. Two research limitations are also provided with the conclusions.