Maryam Ghasemaghaei

Online information quality and consumer satisfaction

A meta-analysis is conducted of the relation between online IQ and satisfaction.Contextual moderators for the online IQ and satisfaction relation are explored.Website type moderates the relation between online IQ and satisfaction.IQ categories used moderate the relation between online IQ and satisfaction.Respondent characteristics do not moderate the online IQ and satisfaction relation. A meta-analysis involving 42 articles was performed to study the existence of potential contextual moderators of the relationship between information quality (IQ) and consumer satisfaction in the online environment. A moderator analysis involving website type (retail or e-services), sample characteristics (respondent type and respondent origin) and the IQ categories used (representational and non-representational) in articles revealed that whereas website type and IQ categories moderate the relationship between perceived online IQ and consumer satisfaction, sample characteristics do not. Implications of the results for researchers and practitioners and directions of future research are presented.

Increasing firm agility through the use of data analytics

Agility, which refers to a dynamic capability within firms to identify and effectively respond to threats and opportunities with speed, is considered as a main business imperative in modern business environments. While there is some evidence that information technology (IT) capabilities can help organizations to be more agile, studies have reported mixed findings regarding such effects. In this study, we identify the conditions under which IT capabilities translate into agility gains. We focus on a specific and critical IT capability, the use of data analytics, which is often leveraged by firms to improve decision making and achieve agility gains. We leverage dynamic capability theory to understand the influence of data analytics use as a lower-order dynamic capability on firm agility as a higher-order dynamic capability. We also draw on the fit perspective to suggest that this impact will only accrue if there is a high degree of fit between several elements that are closely related to the use of data analytics tools within firms including the tools themselves, the users, the firm tasks, and the data. The proposed research model is empirically validated using survey data from 215 senior IT professionals confirming the importance of high levels of fit between data analytics tools and key related elements. The findings provide the understanding of the impacts of data analytics use on firm agility, while also providing guidance to managers on how they could better leverage the use of such technologies. These findings could be more broadly used to inform the effective use of other forms of IT in organizations. A theoretical model is developed to study the conditions under which using data analytics leads to higher firm agility.Research model is empirically validated using survey data from 215 senior IT professionals.Higher levels of fit between data analytics tools and data, people, and tasks are critical for improving firm agility.At low levels of fit between analytics tools and data, people, and tasks firm agility could actually be undermined.

Data analytics competency for improving firm decision making performance

The concept of Data Analytics (DA) competency has been conceptualized and validated.The impact of DA competency on decision making performance is empirically examined.All dimensions of DA competency significantly improve decision quality.All dimensions, except bigness of data, significantly increase decision efficiency. This study develops and validates the concept of Data Analytics Competency as a five multidimensional formative index (i.e., data quality, bigness of data, analytical skills, domain knowledge, and tools sophistication) and empirically examines its impact on firm decision making performance (i.e., decision quality and decision efficiency). The findings based on an empirical analysis of survey data from 151 Information Technology managers and data analysts demonstrate a large, significant, positive relationship between data analytics competency and firm decision making performance. The results reveal that all dimensions of data analytics competency significantly improve decision quality. Furthermore, interestingly, all dimensions, except bigness of data, significantly increase decision efficiency. This is the first known empirical study to conceptualize, operationalize and validate the concept of data analytics competency and to study its impact on decision making performance. The validity of the data analytics competency construct as conceived and operationalized, suggests the potential for future research evaluating its relationships with possible antecedents and consequences. For practitioners, the results provide important guidelines for increasing firm decision making performance through the use of data analytics.

Reviews’ length and sentiment as correlates of online reviews’ ratings

The purpose of this paper is twofold: first, to identify and validate reviews’ length and sentiment as correlates of online reviews’ ratings; and second, to understand the emotions embedded in online reviews and how they associate with specific words used in such reviews.,A panel data set of customer reviews was collected for auto, life, and home insurance from January 2012 to December 2015 using a web scraping technique. Using a sentiment analysis approach, 1,584 reviews for the auto, home, and life insurance services of 156 insurance companies were analyzed.,The results indicate that, since 2013, consumers have generally had more negative emotions than positive ones toward insurance services. The results also show that consumer review sentiment correlates positively and review length correlates negatively with consumer online review ratings. Furthermore, a two-way ANOVA analysis shows that, in general, short reviews with positive sentiment are associated with high review ratings.,The findings of this study provide service companies, in general, and insurance companies, in particular, with important guidelines that should be considered to increase consumers’ positive attitude toward their services.,This paper highlights the importance of sentiment analysis in identifying consumer reviews’ emotions and understanding the associations and interactions of reviews’ length and sentiment on online review rating, which can lead to improved marketing strategies.

Improving Organizational Performance Through the Use of Big Data

ABSTRACT The number of firms that plan to invest in big data usage has been reduced as many of them are still trying to understand the necessary conditions needed to improve their performance through the processing and use of big data. In this study, we leverage the resource-based view to investigate the role of tools sophistication, big data utilization, and employee analytical skills in improving organizational performance. The research model is validated empirically from 140 senior IT professionals using survey data. The findings show that when firms process big data, organizational performance is at its highest when firms use sophisticated tools, while this is not the case when firms do not process big data. Furthermore, findings show that, interestingly, at the lower levels of employee analytical skills, there is no significant impact of big data utilization on organizational performance, suggesting important implications for theory and for the guidance of business action.