Human-Machine Function Allocation In Information Systems: A Comprehensive Approach

In the past, information systems development methodologies primarily focus on whether the needs of an organization could be met. In recent years, several human-centered systems development methodologies are developed to emphasize both organizational and human needs. In addition to an information system being useful, its usability become a central concern, and user analysis and task analysis are important parts in these methodologies. Human-machine function allocation is an important aspect of task analysis. Yet, current research and practice in this area show a gap for systematic and consistent guidelines and approaches. To address this gap, this paper proposes three guidelines and a comprehensive approach for human-machine function allocation when designing organizational information systems. Built on Price’s decision matrix, Levels of Automation, and the Analytic Hierarchy Process (AHP), our approach consists of four steps in determining human-machine function allocation. To illustrate this approach, an application example is provided

WHAT AND HOW AFFECT INFLUENCE THE CONSEQUENCE OF PRODUCT TRIAL

IT product trial is an important method to promote consumers’ attitude toward IT product. Affect is one of the most essential factors and components in determining consumers’ attitude. However, previous studies pay more attention to the affective response to trial, which measure the holistic feeling about product trial experience. Affect in product trial is complex and multipartite that different parts may have different influence on consumers’ attitude. Therefore, we build the Affective Response Framework to divide consumers’ affect into affective response to product, affective response to behaviour, and affective response to environment. And then we analyse the relationship between three components of affective response and consumers’ attitude. In order to test the hypothesis, we launch a field study of new IT product trial (an electroencephalogram product) among 205 college students. Results reveal that affective response to product and behaviour have positive influence on attitude toward product; affective response to behaviour and environment have positive influence on attitude toward trial

Examining the Influencing Factors of Cross-Project Knowledge Transfer: An Empirical Study of IT Service Firms

Despite the significance of knowledge transfer in IT service industry, our understanding of knowledge transfer between projects remains limited. Different from the existing studies mainly examining knowledge transfer at organizational level or at individual level within the same project team, this study examines the factors that influence cross-project knowledge transfer in IT service firms. Based on the process logic of knowledge transfer, we develop an integrated theoretical model that posits that cross-project knowledge transfer is influenced by knowledge, transfer activities, project teams’ transfer capabilities, project team context and project task context. We use the recipient IT project implementation performance to measure the effectiveness of cross-project knowledge transfer. Results of the preliminary test show that the designed questionnaires have scalability for the latent constructs, and the theoretical model has its rationality to some extent. To fully assess our proposed research model, we will collect large data set and perform a complete data analysis to test our model. Our study contributes to existing research by focusing on cross-project knowledge transfer and empirically investigating the performance effect of project-related factors. Results of the study will have important implications for IT practitioners

A Typology Of Online Window Shopping Consumers

Consumer online shopping behaviors are well attended in the IS and marketing literature. Yet, there is another group of individuals who spend a lot of time online but do not purchase anything. This online window shopping phenomenon is intriguing to both scholars and marketers yet it is less studied and little understood. Questions such as what the online window shopping consumers do during their visits, how to differentiate their activities and how to design marketing strategies to stimulate them to buy are all essential and beg for investigation. To address this gap, we propose a typology of online window shopping consumers based on the Consumer Information Processing Model, then empirically validate and refine the typology using a set of clickstream data. The final typology contains four main types of online window shopper consumers: 1) promotion finders, 2) social & hedonic experience seekers, 3) information gatherers, and 4) learners & novices. This study extends consumer online behavior research in both e-commerce and social commerce by focusing on the specific group of consumers who only do online window shopping. Besides theoretical contributions, the findings also provide marketers and businesses with valuable references for designing targeted marketing strategies or promotional activities for online window shopping consumers

ACQR: A Novel Framework to Identify and Predict Influential Users in Micro-Blogging

As key roles of online social networks, influential users in micro-blogging have the ability to influence the attitudes or behaviour of others. When it comes to marketing, the users’ influence should be associated with a certain topic or field on which people have different levels of preference and expertise. In order to identify and predict influential users in a specific topic more effectively, users’ actual influential capability on a certain topic and potential influence unlimited by topics is combined into a novel comprehensive framework named “ACQR” in this research. ACQR framework depicts the attributes of the influentials from four aspects, including activeness (A), centrality (C), quality of post (Q) and reputation (R). Based on this framework, a data mining method is developed for discovering and forecasting the top influentials. Empirical results reveal that our ACQR framework and the data mining method by TOPSIS and SVMs (with polynomial and RBF kernels) can perform very well in identifying and predicting influential users in a certain topic (such as iPhone 5). Furthermore, the dynamic change processes of users’ influence from longitudinal perspective are analysed and suggestions to the sales managers are provided

Research on Internet Addiction Behaviors and Coping Strategies of the Seniors based on Grounded Theory

[Purpose/Significance] Under the background of the rapid penetration of the Internet and the aging transformation, the digital divide and Internet addiction of the seniors coexist, and the emerging phenomenon of Internet addiction of the seniors has many potential hazards, which need to be studied urgently. [Method/Process] This study crawled from the Internet published cases of the seniors’ Internet addiction and experts’ analysis opinions, adopted the grounded theory qualitative analysis method, studied the influential factors, behavioral characteristics, adverse consequences and coping strategies of the seniors’ Internet addiction, and constructed a behavioral model and a coping model of Internet addiction among the seniors. [Result/Conclusion] Individual factors (needs and abilities) and contextual factors (IT factors and living factors) jointly affect the formation of the seniors’ Internet addiction behaviors. It is necessary to adopt the multi-subject linkage and collaborative governance, adopt the strategies of satisfying the needs of emotional relationship, promoting the seniors’ digital inclusion, transforming the Internet care for the seniors and optimizing the seniors’ living space, so as to guide the seniors to use the Internet correctly and build an age-friendly digital inclusive society

INTEGRATING DIFFERENT TYPES OF TARGETING METHODS IN ONLINE ADVERTSING

Rule based targeting, behavioural targeting, and contextual targeting are three different types of targeting methods, delivering customized ads based on different categories of variables. A rule based targeting method uses viewers’ own characteristics, while behavioural targeting delivers ads based on previous content users have browsed. At the same time, contextual targeting uses the characteristics of the webpage on which an ad will be displayed to decide which ads to display. On the other hand, all the three categories of factors and the interaction among them could impact the effectiveness of an online displaying ad. For organizations seeking to optimize their online marketing effort, it therefore becomes crucial to have a thorough understanding on how the variables from individual, behavioural, and contextual aspects moderate the effectiveness of a targeting method based on variables in other categories. But we have not yet found any study provides a theoretic framework to support such understanding. This paper thus proposes to investigate the moderation effect of variables in different categories on the effectiveness of a targeting method based on variables from other categories by using cookie-based data collected by an online marketing firm for its online displaying ads

KNOWLEDGE SHARING OF SENIOR EMPLOYEES IN THE CONTEXT OF TASK-BASED COOPERATION: A GAME THEORETIC ANALYSIS

The aging of population has become a global trend and the critical knowledge of enterprises may be lost with the retirement of senior employees. Task-based cooperation is an important method to prevent the loss of knowledge and to promote the knowledge sharing behavior between senior employees and young ones. This paper constructs the knowledge contribution payoff functions of senior employees and young ones in the context of task-based cooperation and analyzes the knowledge contribution behavior using static game theory with complete information, and then we obtain Nash equilibrium solutions under different conditions. The results suggest that enterprises can promote knowledge contribution of senior employees and young ones in the process of task-based cooperation by improving social rate of return(e.g., creating a good cultural atmosphere), reducing cost rate of knowledge contribution (e.g., training on knowledge expression), raising economic rate of return and providing monetary compensation according to the contribution of knowledge, whether the marginal payoff of employees’ knowledge contribution is increasing, invariant or diminishing. Since the formation of social return is difficult in the short term, giving economic incentives can be an effective way at the beginning. With the progress of task-based cooperation between senior employees and young ones, the amount of employees’ knowledge (especially of young ones’), the productivity of knowledge contribution, the collaborative efficiency and social rate of return will increase and therefore economic incentives contributing to cooperation between both players may decrease appropriately. The findings of this paper are beneficial to understand knowledge sharing behavior in the context of task-based cooperation, and provide several incentive mechanisms for enterprises to promote knowledge sharing between senior employees and young ones