Actualizing big data analytics affordances: A revelatory case study

Dremel, Christian; Herterich, Matthias M.; Wulf, Jochen; Brocke, Jan vom

doi:10.1016/j.im.2018.10.007

Cited by 108 publications

(93 citation statements)

References 86 publications

(159 reference statements)

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“…For example, Zammuto et al (2007) provide five examples of organizational affordances offered by information technologies: work process visualization, real-time innovation, virtual collaboration, mass collaboration, and simultaneous synthetic representation. More recent contributions shed light on new organizational affordances offered by BDTA: Lehrer et al (2018) use qualitative case studies to conceptually describe two important clusters of big data affordances in service companies: service automation and human-machine service practices; Dremel et al (2020) analyzed four big data affordances for automotive companies: establishing customer-centric marketing, provisioning vehicle-data-driven services, data-driven vehicle developing, and optimizing production processes.…”

Section: Conceptual and Quantitativementioning

confidence: 99%

“…As big data affordances are possibilities for action offered by BDTA to organizations, their number is potentially indefinite, as firms' goals, capabilities, and competitive contexts are various and constantly changing (Majchrzak and Markus 2013). For this reason, affordance theory research typically targets sub-sets of affordances with a highly granular approach that captures the relevant possibilities for action within a given actor/time/space frame (Dremel et al 2020;Lehrer et al 2018;Majchrzak and Markus 2013;Strong et al 2014).…”

Section: Rationale Of the Scale Development Processmentioning

confidence: 99%

“…The current understanding of the process through which big data investments pay off emerges from three research streams. First, information systems (IS) scholars recently started to describe the organizational affordances enabled by big data investments (Dremel et al 2020;Lehrer et al 2018). Affordances are defined as possibilities for action offered by a given technology to a goal-directed actor with certain capabilities (Volkoff and Strong 2018).…”

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confidence: 99%

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How and when do big data investments pay off? The role of marketing affordances and service innovation

Luca

Herhausen

Troilo

et al. 2020

J. of the Acad. Mark. Sci.

116

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Big data technologies and analytics enable new digital services and are often associated with superior performance. However, firms investing in big data often fail to attain those advantages. To answer the questions of how and when big data pay off, marketing scholars need new theoretical approaches and empirical tools that account for the digitized world. Building on affordance theory, the authors develop a novel, conceptually rigorous, and practice-oriented framework of the impact of big data investments on service innovation and performance. Affordances represent action possibilities, namely what individuals or organizations with certain goals and capabilities can do with a technology. The authors conceptualize and operationalize three important big data marketing affordances: customer behavior pattern spotting, real-time market responsiveness, and data-driven market ambidexterity. The empirical analysis establishes construct validity and offers a preliminary nomological test of direct, indirect, and conditional effects of big data marketing affordances on perceived big data performance. Keywords Big data technologies and analytics. Affordance theory. Marketing affordances. Service innovation. Big data performance. Industry digitalization "There is nothing so practical as a good theory (Kurt Lewin)." More and better customer data have long been marketers' holy grail when such information was scarce. Firms are now investing significant resources into big data technologies and analytics (BDTA), following the assumption that they may drive superior performance (Lambrecht and Tucker 2015), enable business transformation (Davenport and Bean 2019), and facilitate disruptive business model innovations (Sorescu 2017). This is particularly evident in the service industry, where BDTA are changing the nature of the customer-firm connection, thereby disrupting existing value propositions (Huang and Rust 2017). Yet, the accelerating rate of big data investments is not always matched by an increased quality and effectiveness of marketing decisions (Shah et al. 2012), and senior managers report mixed perceptions of the extent to which big data contribute to a firm's performance (Bean and Davenport 2019). 1 Hence, developing a better understanding 1 According to a recent survey of senior executives in Fortune 1000 and industry-leading US firms, 91.6% of companies are accelerating the pace of big data investments. However, only 62.2% report measurable results from these investments; 59.5% declare to drive innovation with data, 47.6% claim to be competing on data and analytics, and only 31% perceive themselves as a data-driven organization (Davenport and Bean 2019).

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Section: Conceptual and Quantitativementioning

confidence: 99%

Section: Rationale Of the Scale Development Processmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

How and when do big data investments pay off? The role of marketing affordances and service innovation

Luca

Herhausen

Troilo

et al. 2020

J. of the Acad. Mark. Sci.

116

View full text Add to dashboard Cite

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“…For example, Ferraris, et al [76] have found that knowledge management orientation can play a significant role in increasing the impact of big data analytics capabilities and firm performance [76]. In another study, Dremel, et al [78] found that actualizing big data analytics affordances in companies can be affected by various social and technical elements, for example, human resources expertise, organizational processes, and social capabilities. Thus, studying the socio-technical aspect can be a direction for future research on big data analytics at the organizational level.…”

Section: Discussion Future Research Directions and Conclusionmentioning

confidence: 99%

“…Based on the result obtained from current systematic research work, this study recommends that future scholars conduct more systematic and empirical studies on the use of big data analytics in diverse types and sizes of companies to explore what other factors may help an organization to amplify the adoption of big data analytics for improvement of their performance. Future scholars may expand the domain of search of big data analytics and business analytics in the area of business and management to capture more studies including those missing in WoS Core Collection as other research works have not appeared in our search result but deserve to be reviewed systematically (for example, Refs [7,8,70,76,[78][79][80]).…”

Section: Discussion Future Research Directions and Conclusionmentioning

confidence: 99%

Big Data Analytics and Firm Performance: A Systematic Review

et al. 2019

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The literature on big data analytics and firm performance is still fragmented and lacking in attempts to integrate the current studies’ results. This study aims to provide a systematic review of contributions related to big data analytics and firm performance. The authors assess papers listed in the Web of Science index. This study identifies the factors that may influence the adoption of big data analytics in various parts of an organization and categorizes the diverse types of performance that big data analytics can address. Directions for future research are developed from the results. This systematic review proposes to create avenues for both conceptual and empirical research streams by emphasizing the importance of big data analytics in improving firm performance. In addition, this review offers both scholars and practitioners an increased understanding of the link between big data analytics and firm performance.

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Mechanisms fostering the sustainability of actualized value propositions of implemented e‐Government projects in Sub‐Saharan Africa: A realist evaluation case of Nigeria and Rwanda

Chidama

Ononiwu

2022

E J Info Sys Dev Countries

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This study examines the mechanisms fostering sustainable value propositions of implemented e‐Governments projects in sub‐Saharan Africa (SSA) as a research focus. Value propositions identify how public organizations use e‐Government to fulfill citizens' needs across different roles. Using a concept‐centric systematic review, we identified such value propositions as effective public organizations, quality service delivery, open government and democratic values, as well as social values and well‐being. We chose some selected e‐Government projects in Nigeria and Rwanda; adopted realist evaluation (RE) multiple case studies as a methodology and introduced affordance actualization, self‐determination theory, and sustainability framework for e‐Government success as theoretical lenses. To collect data, we adopted a mixed method RE approach and used a contingent valuation method (CVM) as a quantitative aspect to identify the actualized value propositions in operations in the implemented e‐Government projects in Nigeria and Rwanda as outcomes. Sequentially followed by a realist interview as a qualitative approach to collect and analyze data we uncovered the generative mechanisms causing such outcomes to exist and be sustainable. Our findings revealed technological cognizance and autonomy as well as competence as individual mechanisms identified for sustaining such outcomes. While organizational mechanisms revealed are continuous availability of funds, institutional, administrative, and coordinating capacity with leadership and political support. Other organizational mechanisms include institutionalizing the technology within local settings with ongoing monitoring and improvement evaluation enabled by both internal and external contextual conditions. We synthesized our findings into an actualized value sustainability framework for implemented e‐Government projects in SSA to contribute to academics and practice in ICT4D, particularly RE application in e‐Government study, which is nascent.

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Actualizing big data analytics affordances: A revelatory case study

Cited by 108 publications

References 86 publications

How and when do big data investments pay off? The role of marketing affordances and service innovation

How and when do big data investments pay off? The role of marketing affordances and service innovation

Big Data Analytics and Firm Performance: A Systematic Review

Mechanisms fostering the sustainability of actualized value propositions of implemented e‐Government projects in Sub‐Saharan Africa: A realist evaluation case of Nigeria and Rwanda

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