User costs and bubbles in land markets

In asset markets with speculative behavior, the long-run equilibrium relationship between asset prices and the discounted flow of future rents may become invalid. We distinguish short-term user costs and longer-term user costs with variables that reflect fundamentals. We show how to work around the empirical problem of measuring speculative expectations about asset price changes and derive a simple user cost formula where the asset price change in the short-term relationship comes out as the long-run change in the overall price level.     

Teacher Training and Teacher Optimism about the American Economic System

The amount and type of economic-education training teachers receive have predictable effects on the teachers' optimism about the future of the American economic system.     

Gender Differences in Double Standards

The purpose of the present study is to investigate gender differences in the use of double standards in ethical judgements of questionable conduct instigated by business or consumers. We investigate if consumers are more critical towards unethical corporate versus consumer actions and if these double standards depend on the gender of the respondent. In the first study, we compared evaluations of four specific unethical actions [cfr. DePaulo, 1987, in: J. Saegert (ed.) Proceedings of the Division of Consumer Psychology (American Psychological Association, Washington DC)] instigated by either the consumer or the corporation. In a second study, we investigated the perception of some general consumer and corporate (un)ethical actions in addition to DePaulo’s unethical scenarios. Both researches show that females are less likely to use double standards when it comes to their own (un)ethical behaviour compared to corporate (un)ethical actions. Furthermore, gender differences in the use of double standards depend on the type of unethical behaviour. Limitations and suggestions for further research are discussed.     

Can users embed their user experience in user-generated images? Evidence from JD.com

Nowadays, massive user-generated images (UGIs) are posted online to convey users' experiences with specific brands or products. Thus, this visual information is precious, as it conveys users' actual and subjective feelings about brands and products. Because of the unprecedented quantity of images and the heterogeneity of their content, it is quite challenging for brand marketers and retailers to probe into subjective user experience in large-scale UGIs. To address this gap, this study aims to identify the connection between user experience and different image semantic features (i.e. centrality and richness) by using deep learning models. By employing objective data (8963 images) from JD.com and using deep learning algorithms (faster R-CNN), we found that users with positive user experience prefer to generate high-centrality and high-richness pictures. Our study enriches the relevant literature and provides valuable practical implications for brand marketers and e-commerce retailers. Based on findings of this work, relevant stakeholders can understand their users’ experience better from objective UGIs and devise corresponding recommendation and service strategies.     

Building nightclub brand personality via guest selection

This paper identifies that guest selection at exclusive nightclubs is a brand building process, and that the guests’ primary value to the clubs therefore is the image they bestow on the brand. The paper contributes to theory by providing empirical support for several mechanisms that have previously been stipulated in literature. It validates that companies build brand personality by controlling typical user imagery, and that for self-expressive product categories, negative user stereotypes are particularly powerful. It supports the theory of symbolic brand avoidance, as well as the notion that social rejection encourages people to elevate their perceptions of their rejecters and strengthens their predilection to affiliate with them. For practitioners, the paper shows managers in the hospitality industry that it is possible to build brands by controlling who is allowed to become a brand-user, and under which conditions this applies.     

How to inspire users in virtual travel communities: The effect of activity novelty on users’ willingness to co-create

Virtual travel community managers tend to incorporate a degree of novelty within activity design to foster interaction between users. Little is known of how users respond to these novel activities. Based on customer inspiration theory, this research investigated the mechanisms of activity novelty on users' willingness to co-create and the moderating effect of user regulatory focus and activity goal attainability. Results of three scenario-based experiments revealed that activity novelty positively influenced users’ willingness to co-create via user inspiration. Promotion-focused users were more inspired by novel activities and in turn had a higher willingness to co-create than those were prevention-focused. When activity goal attainability was high (vs. low), the positive effect of activity novelty on inspiration was attenuated. We present the theoretical and practical implications of activity design within virtual travel communities.     

Measuring user similarity using check-ins from LBSN: a mobile recommendation approach for e-commerce and security services

ABSTRACT

Social friendship and geographical position information often reflects individuals’ personal preferences and other types of knowledge that can be used to extract their similarity for recommendation systems. This paper finds that users are more likely to move around some specific centres or check in at some hotspots; a few individuals check in frequently, whereas most locations are rarely visited. Based on these findings, we propose a multi-centre clustering algorithm to capture users’ mobile patterns and develop a user similarity measurement method. Complexity analysis shows the method’s efficiency in handling large datasets and experimental results demonstrate its good applicability.     

How attachment affects user stickiness on live streaming platforms: A socio-technical approach perspective

User stickiness is an important factor in the development of live streaming shopping platforms, which describes the degree of users' attention to the platforms. Although some e-commerce websites have provided live streaming services to improve the purchase experience of consumers, few people know how the services affect user stickiness. Building upon attachment theory and socio-technical approach, we developed a theoretical model to understand how live streaming service affects the user stickiness through users' attachment, which is tested by using 425 live streaming shopping platform's users. The results showed that technical factors (synchronicity and vicarious expression) and social factors (interaction and identification) positively affect emotional attachment to streamers and platform attachment respectively, which in turn increase the user stickiness.     

User voice and complaints as drivers of innovation in public services

User voice and complaints can serve as important inputs to innovation in public services. User knowledge can be harnessed to provide insights and ideas that prompt more effective service responses and add value to service delivery. However, the mechanisms for harnessing user voice and complaints are often not fully understood, and their potential is often underdeveloped. This paper elaborates a conceptual framework which maps the processes by which user voice and complaints might prompt effective public service innovation. Six practical real-world examples are then presented and analysed to illuminate discussion of some critical success factors for consumer-knowledge-enabled innovation.     

A novel discrete network design problem formulation and its global optimization solution algorithm

Conventional discrete transportation network design problem deals with the optimal decision on new link addition, assuming the capacity of each candidate link addition is predetermined and fixed. In this paper, we address a novel yet general discrete network design problem formulation that aims to determine the optimal new link addition and their optimal capacities simultaneously, which answers the questions on whether a new link should be added or not, and if added, what should be the optimal link capacity. A global optimization method employing linearization, outer approximation and range reduction techniques is developed to solve the formulated model.