I like it because I (‘m) like You – measuring user attitudes towards information on Facebook

Limited in motivation and cognitive ability to process the increasing amount of information on their Newsfeed, users apply heuristic processing to form their attitudes. Rather than extensively analysing the content, they increasingly rely on heuristic cues – such as the amount of comments and likes as well as the level of relationship with the “poster” – to process the incoming information. In the paper we explore what impact these heuristic cues have on the affective and cognitive attitude of users towards the posts on their Newsfeed. We conduct a survey on based on a Facebook application that allows users to evaluate Newsfeed posts in real time. Applying two distinct panel-regression methods we report robust results that indicate that there is a certain relationship primacy effect when users are processing information: only if the level of relationship with the “poster” is low, the impact of comments and likes on the attitude is considered, whereby likes trigger positive, whereas comments – negative evaluations.

Cognition or Affect? - Exploring Information Processing on Facebook

Recognizing the increasing amount of information shared on Social Networking Sites (SNS), in this study we aim to explore the information processing strategies of users on Facebook. Specifically, we aim to investigate the impact of various factors on user attitudes towards the posts on their Newsfeed. To collect the data, we program a Facebook application that allows users to evaluate posts in real time. Applying Structural Equation Modeling to a sample of 857 observations we find that it is mostly the affective attitude that shapes user behavior on the network. This attitude, in turn, is mainly determined by the communication intensity between users, overriding comprehensibility of the post and almost neglecting post length and user posting frequency.

Investigation of the Network Construction Behaviour on Social Networking Sites

By enabling connections between individuals, Social Networking Sites, such as Facebook, promise to create significant individual as well as social value. Encouraging connections between users is also crucial for service providers who increasingly rely on social advertising and viral marketing campaigns as important sources of their revenue. Consequently, understanding user’s network construction behavior becomes critical. However, previous studies offer only few scattered insights into this research question. In order to fill this gap, we employ Grounded Theory methodology to derive a comprehensive model of network construction behavior on social networking sites. In the following step we assess two Structural Equation Models to gain refined insights into the motivation to send and accept friendship requests – two network expansion strategies. Based on our findings, we offer recommendations for social network providers.

Leveraging Trust and Privacy Concerns in Online Social Networks: an Empirical Study

Unprecedented success of Online Social Networks, such as Facebook, has been recently overshadowed by the privacy risks they imply. Weary of privacy concerns and unable to construct their identity in the desired way, users may restrict or even terminate their platform activities. Even though this means a considerable business risk for these platforms, so far there have been no studies on how to enable social network providers to address these problems. This study fills this gap by adopting a fairness perspective to analyze related measures at the disposal of the provider. In a Structural Equation Model with 237 subjects we find that ensuring interactional and procedural justice are two important strategies to support user participation on the platform.

Privacy Calculus on Social Networking Sites: Explorative Evidence from Germany and USA

Worldwide social networks, like Facebook, face fierce competition from local platforms when expanding globally. To remain attractive social network providers need to encourage user self-disclosure. Yet, little research exists on how cultural differences impact selfdisclosure on these platforms. Addressing this gap, this study explores the differences in perceptions of disclosure-relevant determinants between German and US users. Survey of Facebook members indicates that German users expect more damage and attribute higher probability to privacy-related violations. On the other hand, even though American users show higher level of privacy concern, they extract more benefits from their social networking activities, have more trust in the service provider and legal assurances as well as perceive more control. These factors may explain a higher level of self-disclosure indicated by American users. Our results provide relevant insights for the social network providers who can adjust their expansion strategy with regard to cultural differences.

‘Stop spamming me!’: exploring information overload on Facebook

The problem of information overload on Facebook is exacerbating as users expand their networks. Growing quantity and increasingly poor quality of information on the Newsfeed may interfere with the hedonic experience of users resulting in frustration and dissatisfaction. In the long run, such developments threaten to undermine sustainability of the platform. To address these issues, our study adopts a grounded theory approach to explore the phenomenon of information overload on Facebook. We investigate main sources of information overload, identify strategies users adopt to deal with it as well as possible consequences. In-depth analysis of the phenomenon allows us to uncover individual peculiarities for identification of relevant information. Based on them we provide valuable recommendations for network providers.

Mehr Geld im Portemonnaie und weniger Sorgen im Gepäck

Der Einsatz von Open Source Software kann das IT-Budget schonen, wenn man richtig vorgeht. Viel wichtiger sind aber strategische Vorteile wie die digitale Nachhaltigkeit oder die Unabhängigkeit von Herstellern, die sich durch den konsequenten Einsatz von Open Source ergeben.

Investigating the value of privacy on online social networks: conjoint analysis

Popularity of Online Social Networks has been recently overshadowed by the privacy problems they pose. Users are getting increasingly vigilant concerning information they disclose and are strongly opposing the use of their information for commercial purposes. Nevertheless, as long as the network is offered to users for free, providers have little choice but to generate revenue through personalized advertising to remain financially viable. Our study empirically investigates the ways out of this deadlock. Using conjoint analysis we find that privacy is indeed important for users. We identify three groups of users with different utility patterns: Unconcerned Socializers, Control-conscious Socializers and Privacy-concerned. Our results provide relevant insights into how network providers can capitalize on different user preferences by specifically addressing the needs of distinct groups in the form of various premium accounts. Overall, our study is the first attempt to assess the value of privacy in monetary terms in this context.

Vertical integration and information sharing — an empirical investigation in the German apparel industry

Despite the astounding success of the fast fashion retailers, the management practices leading to these results have not been subject to extensive research so far. Given this background, we analyze the impact of information sharing and vertical integration on the performance of 51 German apparel companies. We find that the positive impact of vertical integration is mediated by information sharing, i.e. that the ability to improve the information flow is a key success factor of vertically integrated apparel supply chains. Thus, the success of an expansion strategy based on vertical integration critically depends on effective ways to share logistical information.

"It won't happen to me!": self-disclosure in online social networks

Despite the considerable amount of self-disclosure in Online Social Networks (OSN), the motivation behind this phenomenon is still little understood. Building on the Privacy Calculus theory, this study fills this gap by taking a closer look at the factors behind individual self-disclosure decisions. In a Structural Equation Model with 237 subjects we find Perceived Enjoyment and Privacy Concerns to be significant determinants of information revelation. We confirm that the privacy concerns of OSN users are primarily determined by the perceived likelihood of a privacy violation and much less by the expected damage. These insights provide a solid basis for OSN providers and policy-makers in their effort to ensure healthy disclosure levels that are based on objective rationale rather than subjective misconceptions.

Modeling microblogging adoption in the enterprise

Despite a broad range of collaboration tools already available, enterprises continue to look for ways to improve internal and external communication. Microblogging is such a new communication channel with some considerable potential to improve intra-firm transparency and knowledge sharing. However, the adoption of such social software presents certain challenges to enterprises. Based on the results of four focus group sessions, we identified several new constructs to play an important role in the microblogging adoption decision. Examples include privacy concerns, communication benefits, perceptions regarding signal-to-noise ratio, as well codification effort. Integrating these findings with common views on technology acceptance, we formulate a model to predict the adoption of a microblogging system in the workspace. Our findings serve as an important guideline for managers seeking to realize the potential of microblogging in their company.

Enterprise software adoption and perceived business performance — an empirical investigation in Germany and the U.S.

This work contributes to the ongoing debate on the productivity paradox by considering CIOs’ perceptions of IT business value. Applying regression analysis to data from an international survey, we study how the adoption of certain types of enterprise software affects the CIOs’ perception of the impact of IT on the firm’s business activities and vice versa. Other potentially important factors such as country, sector and size of the firms are also taken into account. Our results indicate a more significant support for the impact of perceived IT benefits on adoption of enterprise software than vice versa. CIOs based in the US perceive IT benefits more strongly than their German counterparts. Furthermore, certain types of enterprise software seem to be more prevalent in the US.

Why participate in an online social network: an empirical analysis

Despite their enormous success the motivation behind user participation in Online Social Networks is still little understood. This study explores a variety of possible incentives and provides an empirical evaluation of their subjective relevance. The analysis is based on survey data from 129 test subjects. Using Structural Equation Modeling, we identified that the satisfaction of the needs for belongingness and the esteem needs through self-presentation together with peer pressure are the main drivers of participation. The analysis of a sub-sample of active users pointed out the satisfaction of the cognitive needs as an additional participation determinant. Based on these findings, recommendations for online social network providers are made.

Drivers of RFID adoption in the automotive industry

The automotive industry is confronted with increasing competition, leading to higher cost pressures and the demand to optimize production processes and value chains. Here the RFID technology promises to improve a range of processes in logistics and manufacturing. Despite its promising potential in the automotive industry, RFID has not yet made a decisive step from pilots to real-life implementations in the supply chain. Building on existing models of technology adoption, we analyze RFID adoption dynamics in the automotive industry. Building on existing IOS adoption models tailored to RFID specifics and based on ten semi-structured interviews with OEMs and suppliers, we evaluate main drivers of RFID adoption in the automotive industry. Our key findings are that the use of a coercive approach by the OEM could be redundant because of the market-driven RFID adoption among many suppliers. Furthermore, suppliers implementing RFID can now gain an early mover competitive advantage by developing higher trust in their relationship with the OEM as well as accumulating unique expertise in this area.