Han-fen Hu

Examining the role of information technology in cultivating firms' dynamic marketing capabilities

Most prior research has investigated an organizations dynamic capabilities in general and overlooked their effect on critical business functions. Our study considered the role of IT in improving firms dynamic marketing capabilities. We developed a model consisting of market orientation, IT infrastructure capabilities, and the use of IT in customer relationship management (CRM). With data collected from 135 manufacturing and service firms in Taiwan, our results supported most of our hypotheses. Our results showed important direct effects of a firms market orientation, use of IT to support CRM, and the functionality of IT infrastructure capabilities on its dynamic marketing capabilities.

Beyond likes and tweets

Online consumer engagement behavior (CEB) affects future economic performance.CEB on Facebook and YouTube positively correlate with movie box-office revenue.Social media-based CEB is critical to improve economic performance of movie firms. This study examines the effects of social media, from the perspective of consumer engagement behavior (CEB), to investigate how CEB is associated with economic performance. Based on social media activities surrounding US movies, we used ordinary least square (OLS) regression models and found that CEB on Facebook and YouTube positively correlate with box-office gross revenue; however, the same effect was not observed on Twitter. This study proposed and tested a set of metrics for CEB on social media, and also provided empirical support for associating CEB with economic performance. The results underscore the importance of investing in social media communication across multiple channels.

A Data-Driven Approach to Measure Web Site Navigability

Web site navigability refers to the degree to which a visitor can follow a Web sites hyperlink structure to successfully find information with efficiency and ease. In this study, we take a data-driven approach to measure Web site navigability using Web data readily available in organizations. Guided by information foraging and information-processing theories, we identify fundamental navigability dimensions that should be emphasized in metric development. Accordingly, we propose three data-driven metrics—namely, power, efficiency, and directness—that consider Web structure, usage, and content data to measure a Web sites navigability. We also develop a Web mining-based method that processes Web data to enable the calculation of the proposed metrics. We further implement a prototype system based on the Web mining-based method and use it to assess the navigability of two sizable, real-world Web sites with the metrics. To examine the analysis results by the metrics, we perform an evaluation study that involves these two sites and 248 voluntary participants. The evaluation results show that user performance and assessments are consistent with the analysis results revealed by our metrics. Our study demonstrates the viability and practical value of data-driven metrics for measuring Web site navigability, which can be used for evaluative, diagnostic, or predictive purposes.

Agency satisfaction with electronic record management systems: A large-scale survey

A huge number of informal messages are posted every day in social network sites, blogs, and discussion forums. Emotions seem to be frequently important in these texts for expressing friendship, showing social support or as part of online arguments. Algorithms to identify sentiment and sentiment strength are needed to help understand the role of emotion in this informal communication and also to identify inappropriate or anomalous affective utterances, potentially associated with threatening behavior to the self or others. Nevertheless, existing sentiment detection algorithms tend to be commercially oriented, designed to identify opinions about products rather than user behaviors. This article partly fills this gap with a new algorithm, SentiStrength, to extract sentiment strength from informal English text, using new methods to exploit the de facto grammars and spelling styles of cyberspace. Applied to MySpace comments and with a lookup table of term sentiment strengths optimized by machine learning, SentiStrength is able to predict positive emotion with 60.6p accuracy and negative emotion with 72.8p accuracy, both based upon strength scales of 1–5. The former, but not the latter, is better than baseline and a wide range of general machine learning approaches.

Examining Agencies’ Satisfaction with Electronic Record Management Systems in e-Government: A Large-Scale Survey Study

While e-government is propelling and maturing steadily, advanced technological capabilities alone cannot guarantee agencies’ realizing the full benefits of the enabling computer-based systems. This study analyzes information systems in e-government settings by examining agencies’ satisfaction with an electronic record management system (ERMS). Specifically, we investigate key satisfaction determinants that include regulatory compliance, job relevance, and satisfaction with support services for using the ERMS. We test our model and the hypotheses in it, using a large-scale survey that involves a total of 1,652 government agencies in Taiwan. Our results show significant effects of regulatory compliance on job relevance and satisfaction with support services, which in turn determine government agencies’ satisfaction with an ERMS. Our data exhibit a reasonably good fit to our model, which can explain a significant portion of the variance in agencies’ satisfaction with an ERMS. Our findings have several important implications to research and practice, which are also discussed.

Examining the Mediating Roles of Cognitive Load and Performance Outcomes in User Satisfaction with a Website: A Field Quasi-Experiment

Navigation structure and user familiarity are critical for user satisfaction, yet the mediating mechanisms by which they affect satisfaction remain unclear, especially from a cognitive perspective. To extend understanding of the drivers of user satisfaction with a website, this study focuses on the mediating roles of cognitive load and performance outcomes (in the form of efficiency and accuracy), according to a cognitive cost–benefit framework and cognitive load theory. The hypotheses were tested with data from a field quasi-experiment among 238 participants using two websites. The results indicated that cognitive load and performance outcomes fully mediated the effect of user familiarity on user satisfaction, and that cognitive load partially mediated the impact of navigation structure. In addition, the mediating effect of cognitive load appeared stronger than that of performance outcomes. Overall, the cognitive cost–benefit framework sheds light on the underlying influence processes and mechanisms by which navigation structure and user familiarity affect user satisfaction. The findings reveal that costs might have more profound influences on user satisfaction in an information-seeking context than benefits do.

Will They Walk or Will They Talk? Comparing Chinese and American Consumers

As the business world becomes less company driven and more customer-oriented, increasing loyalty becomes a critical factor to building a successful company (Zahay et al. 2012). Such loyalty is not easy to earn, but in the increasingly socially connected world, customers who are brand advocates serve as a key marketing tool (Sen and Lerman 2007). In effect, as a free resource that consumers can avail of at any time and from multiple sources, word of mouth (WOM) not only allows customers to tell their consumption stories and share their opinions, but it also allows them to research a seemingly independent view of a business (Moore 2012). As such, research abounds on the motivations driving WOM, whether positive or negative, such as self-enhancement, anger and retaliation, altruism, brand love, and many others (De Angelis et al. 2012).

Examining Firms’ Green Information Technology Practices: A Hierarchical View of Key Drivers and Their Effects

Abstract This study examines key drivers of firms’ green information technology (IT) practices. A hierarchical view, premised in institutional theory and competitive dynamics, leads to a model that explains firms’ practices. This model includes factors that pertain to the environment (environmental awareness and government regulations), industry (industry norms and competitors’ green practices), and firm (customers’ and equity holders’ attitudes and internal readiness) levels. Survey data collected from 304 major firms in Taiwan are used to test the model and hypotheses. In particular, attitudes of a firm’s customers and equity holders, as well as its internal readiness, directly influence its green IT practices, while also channeling the effects of important contextual factors. Among the contextual factors considered herein, environmental awareness and industry norms influence firms’ practices both directly and indirectly. The overall results highlight the significance of contextual factors and underscore the mediating roles of firm-specific considerations. According to our findings, firms should implement strategic goals and make resource allocations toward green IT practices that are aligned with the industry-wide atmosphere and general public’s awareness of environmental protection.