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Considering the cognitive challenges associated with a data-rich business environment, this research aims to investigate the relationship between data literacy (DL), perceived data overload (PDO), and technostress (TS), besides the effect of these constructs on professional's individual performance (IP).

Through survey research, the authors collected data from 321 professionals who work in data-rich and highly technological business environments. To test the hypotheses proposed, the authors developed the partial least squares structural equation modeling (PLS-SEM) procedures.

The results showed that DL is positively associated with IP and negatively with PDO. PDO is positively associated with TS and negatively with IP. The authors found no significant negative association between TS and IP.

With this research, the authors seek to contribute to the gap in the literature concerning two cognitive challenges associated with data-rich business environments: PDO and TS, analyzing from the point of view of the individual, and highlighting the importance of DL in this context.

The results can assist managers in effectively being concerned with the DL level of their workforce. This is important considering not only the professionals' IP but also the cognitive challenges such as PDO and TS.

The innovation of this study lies in the empirical analysis of DL in the business context and its relationship with two cognitive challenges inherent in data-rich environments: PDO, and TS. Besides, the authors highlight the importance of understanding such phenomena in terms of IP.

Few well-documented studies have explained the importance of researching firms' marketing analytics capability (FMAC). In spite of its significance, there is scant attention to conceptualising and empirically investigating FMAC and its consequences in a data-driven business context. Thus, this study aims to develop and test a conceptual model that relates FMAC and its repercussions in the data-rich business environment.

This study analysed the data from 250 managers amongst large and medium-sized manufacturing and service-intensive firms. Furthermore, this research performed an empirical study by using operationalised questionnaire survey method to verify the hypotheses and reach its theoretical and managerial implications. Structural equation modelling with maximum-likelihood estimation method was applied to verify the validity of the proposed research model.

Multivariate analysis results show that FMAC significantly influences firms' competitive marketing performance (FCMP) with the presence of holistic marketing decision-making (HMDM) as a mediator. Moreover, adoption of artificial intelligence (AAI) enhances the relationship of FMAC-HMDM and FMAC-FCMP linkages.

This study analyses how FMAC can enhance FCMP and contributes to resource-based views and technological capability theories. From a managerial perspective, guidelines are provided for marketers to adopt advance technologies, such as AI, to optimise FMAC and HMDM to achieve competitive marketing performance.

Believing that “how to be competitive in marketing performance under data-rich-environment”, this research is the first to use the data of a firm manager to facilitate the understanding of FMAC, which provides a new direction for improving marketing performance. In addition, HMDM and AAI are also proposed for firms to optimise FCMP.

Over the last few years, the European Central Bank (ECB) has adopted unconventional monetary policies. These measures aim to boost economic growth and increase inflation through the bond market. The purpose of this paper is to study the impact of the ECB’s quantitative easing (QE) on the investor’s behavior in the stock market.

First, the authors theoretically identify the transmission channels of the QE shocks to the stock market. Then, the authors empirically assess the financial market’s responses to QE shocks in a data-rich environment using a factor augmented VAR (FAVAR).

The results show that the ECB’s unconventional monetary policy positively affects the stock market. A QE shock leads to an increase in stock prices and a drop in the realized volatility and the implied risk premium. The authors also suggest that the ECB’s QE is transmitted to the stock market through five main channels: the liquidity, the expectation, the portfolio reallocation, the interest rates and the risk premium channels.

The findings help to better understand the behavior of stock market assets in a data-rich economic context and guide investors and policymakers in the presence of unconventional monetary tools. For instance, decision-makers and investors should consider the short-term effect of the QE interventions and the changing behavior of the financial actors over time. In addition, high stock market returns can increase risk appetite. This can lead investors to underestimate the market risk. Decision-makers and market participants should take into consideration the impact of the large injection of money through the QE, which may raise the risk of a speculative bubble in the financial market.

To the best of the authors’ knowledge, this is the first study that incorporates a theoretical and empirical analysis to explore QE transmission to the stock market in the European context. Unlike previous studies, the authors use the shadow rate proposed by Wu and Xia (2017) to quantify the effect of the ECB’s QE in a data-rich environment. The authors also include two key risk indicators – the stock market risk premium and the realized volatility – to capture investors’ behavior in the stock market following QE shocks.

Over the last 50 years, increased attention for personalization paved the way for one-to-one marketing efforts, but firms struggle to deliver on this promise. The purpose of this manuscript is to provide a complete picture on personalization, develop a future research agenda and put forth concrete advice on how to move the field forward from a theoretical, methodological, contextual, and practical viewpoint.

This research follows a systematic literature review process, providing an in-depth analysis of 135 articles (covering 184 studies) to distill the (1) key building blocks and components of personalization and (2) theoretical, contextual, and methodological aspects of the studies.

This manuscript uncovers six personalization components that can be linked to two personalization building blocks: (1) learning: manner, transparency, and timing and (2) tailoring: touchpoints, level, and dynamics. For each of these components, the authors propose future research avenues to stimulate personalization research that accounts for challenges in today's data-rich environments (e.g. data privacy, dealing with new data types). A theoretical, contextual, and methodological (i.e. industry, country and personalization object) review of the selected studies leads to a set of concrete recommendations for future work: account for heterogeneity, embed theoretical perspectives, infuse methodological innovation, adopt appropriate evaluation metrics, and deal with legal/ethical challenges in data-rich environments. Finally, several managerial implications are put forth to support practitioners in their personalization efforts.

This research provides an integration of personalization research beyond existing and outdated review papers. Doing so, it accounts for the impact of new technologies and Artificial Intelligence and aims to advance the next generation of knowledge development on personalization.

The marketing information system (MkIS) in the data-rich business environment receives all the attention these days, but as essential and perhaps even more essential is the marketing information system management capability (MkISMC). Although many service firms apprehend the return from MkIS, others clearly struggle. It seems that MkIS management capability dynamics and their direct/indirect holistic influence on service firm's competitive performance (SFCP) are unsolved in the current data-driven service economy. This study aims to conceptualize a model and test the antecedents on service firms' competitive performance.

This study utilizes a survey of a sizeable sample of service firms’ managers at the firm level. A total of 250 useable responses were obtained and analyzed through structural equation modeling.

Results reveal that variables under their respective direct influences are positively and significantly related. Interestingly, MkISMC has a relatively large magnitude of positive and direct effects on service firms' competitive performance. The other variables, such as the use of marketing analytics (UMAN), service innovation and management (SINM), partially mediate the effect of MkISMC on the competitive performance of service firms.

The findings inform practitioners that MkISMC, UMAN and SINM play a vital role in attaining service firms' competitive performance in the data-rich environment. Overall, it deepens the understanding of the mediation effect of UMAN and SINM of service firms on competitive performance.

The study advances theoretical understanding of resource-based view (RBV), market orientation and dynamic capability that formulate the relationship of MkISMC, UMAN and SINM in attaining SFCP in the ever-changing data-driven business economy.

The datafication of teaching and learning settings continues to be of broad interest to the learning sciences. In response, this study aims to explore a non-traditional learning setting, specifically two Golf Teaching and Research Programs, to investigate how athletes and coaches capture, analyze and use performance data to improve their practice. Athletic settings are well known for spurring the proliferation of personal data about performance across a range of contexts and ability levels. In these contexts, interest in athletes’ experiences with data has often been overshadowed by a focus on the technologies capturing the data and their capabilities.

This ethnographic research focuses on the data-rich experiences of golf coaches and students during two pedagogical encounters. Using Balka and Star’s (2015) concept of shadow bodies, this article explores how golfing bodies can become infused with data, creating partial representations of a lived experience that can be augmented and manipulated for pedagogical purposes, depending on the context and the individuals involved.

Interaction analysis helps the authors to examine the embodied and interactional nature of coach-golfer pedagogical encounters across two sites, a local Professional Golf Association golf course and a Swing Analysis Lab. The authors also split these encounters into two episodes to identify how coaches and golfers use partial representations of their bodies to analyze performance and interpret data.

This research suggests that as data-driven practices continue to engulf athletic settings, and teaching and learning settings broadly, emphasis needs to be placed on ensuring that athletes (learners) – from the most recreational to elite users – have an embodied understanding of their performance to improve their ability. Furthermore, this article raises questions about what data gets shared between instructors and athletes and how that data is used.

The purpose of this paper is to demonstrate the value of enriched customer data for analytical customer relationship management (CRM) in the insurance sector. In this study, online quotes from an insurer’s website are evaluated in terms of serving as a trigger event to predict churn, retention, and cross-selling.

For this purpose, the records of online quotes from a Swiss insurer are linked to records of existing customers from 2012 to 2015. Based on the data from automobile and home insurance policyholders, random forest prediction models for classification are fitted.

Enhancing traditional customer data with such additional information substantially boosts the accuracy for predicting future purchases. The models identify customers who have a high probability of adjusting their insurance coverage.

The findings of the study imply that enriching traditional customer data with online quotes yields a valuable approach to predicting purchase behavior. Moreover, the quote data provide supplementary features that contribute to improving prediction performance.

This study highlights the importance of selecting the relevant data sources to target the right customers at the right time and to thus benefit from analytical CRM practices.

This paper is one of the first to investigate the potential value of data-rich environments for insurers and their customers. It provides insights on how to identify relevant customers for ensuing marketing activities efficiently and thus avoiding irrelevant offers. Hence, the study creates value for insurers as well as customers.

Concepts of values-based leadership posit that school principals’ professional practice must be informed by values to ensure coherently purposeful activities. Contingency models stress the contextual dependency of professional practice and the need to match activities to local opportunities and constraints. The purpose of this paper is to reconcile both positions from an integrative perspective and to illustrate examples of “values-based contingency leadership” (Day et al., 2001).

Analyses draw on survey data from 56 German schools in order to relate professional values stated by the principals as well as organizational features of their schools to teacher ratings on leadership behaviour (n=910). Instead of scrutinizing singular variables in isolation, a typological approach serves to identify value profiles as well as organizational configurations. Analyses of variance are applied to examine the combined effects of both factors on leadership behaviour.

Interactional effects in the sample indicate that contextual influences are not homogenous across differing value profiles of principals who operate under equal conditions. Descriptive patterns of leadership behaviour within each organizational configuration reveal how principals accentuate leadership activities according to their value profile.

Due to the low statistical power of the small sample, findings are clearly exploratory in nature. However, replication and extension studies seem fruitful, as effect sizes of value-context interactions are consistent with theoretical assumptions and not artificially inflated by common-source variance.

This paper elaborates and exemplifies the moderating role of values in contextual influences on leadership behaviour. It also provides deeper insights into the content and structure of professional values advocated by school principals.

The purpose of this study is to demonstrate and characterise a soft-tooled micro-injection moulding process through in-line measurements and surface metrology using a data-intensive approach.

A soft tool for a demonstrator product that mimics the main features of miniature components in medical devices and microsystem components has been designed and fabricated using material jetting technique. The soft tool was then integrated into a mould assembly on the micro-injection moulding machine, and mouldings were made. Sensor and data acquisition devices including thermal imaging and injection pressure sensing have been set up to collect data for each of the prototypes. Off-line dimensional characterisation of the parts and the soft tool have also been carried out to quantify the prototype quality and dimensional changes on the soft tool after the manufacturing cycles.

The data collection and analysis methods presented here enable the evaluation of the quality of the moulded parts in real-time from in-line measurements. Importantly, it is demonstrated that soft-tool surface temperature difference values can be used as reliable indicators for moulding quality. Reduction in the total volume of the soft-tool moulding cavity was detected and quantified up to 100 cycles. Data collected from in-line monitoring was also used for filling assessment of the soft-tool moulding cavity, providing about 90% accuracy in filling prediction with relatively modest sensors and monitoring technologies.

This work presents a data-intensive approach for the characterisation of soft-tooled micro-injection moulding processes for the first time. The overall results of this study show that the product-focussed data-rich approach presented here proved to be an essential and useful way of exploiting additive manufacturing technologies for soft-tooled rapid prototyping and new product introduction.

This paper aims to provide a rationale for seeking out and making federal, state and non-governmental Web sites available to social work students and social workers and describe a number of valuable resources, primarily from the non-governmental agencies, as they can be more difficult to identify.

Resources included here include those that illuminate policy issues in general followed by those dealing with specific populations or issues. They have been identified both by systematic study and the serendipity that results from 27 years of experience seeking resources for undergraduate and graduate students in social work.

These Web sites provide timely and authoritative information of particular interest to social work students or practitioners: first, Web sites that help illuminate policy and practices related to supporting low income people; and then, Web sites focusing on specific (geographically or topically) information needs.

The author is most familiar with sources that have been useful to undergraduate social work students and graduate students in a program that focuses on rural social work.

The information in the Web sites described is timely and authoritative and should be part of the resources that are made known to students, faculty and practitioners in this discipline to inform their work.

Not every library can afford to subscribe to the valuable research presented in social work journals. Nor can they afford to purchase every book that might be valuable to social workers. They can, however, be knowledgeable about Web sites that present good, data-rich information as well as models of successful programming and services. In addition, it seems valuable for social workers in one state to build on the ideas that other practitioners are utilizing in another state. These Web sites often provide that kind of cross-pollination.

While the organizations that create these Web sites have been around for decades, the literature in library science focuses primarily on collection development activities around books, electronic books and journals, while the Web sites which are free, authoritative and timely get a lot less attention.