How to improve firm performance using big data analytics capability and business strategy alignment?

May combine two claims.

The entanglement conceptualization of the higher-order BDAC model is valuable and has an impact on firm performance (FPER).

“The findings confirm the value of the entanglement conceptualization of the higher-order BDAC model and its impact on FPER.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Three core themes underpin perceptions of BDA technology capability (BDATEC): connectivity, compatibility, and modularity.

“Three core themes underpin perceptions of BDATEC: connectivity, compatibility and modularity.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Four core themes constitute perceptions of BDA management capability (BDAMAC): BDA planning, investment, coordination, and control.

“Four core themes were found to constitute perceptions of BDAMAC; these were termed as BDA planning, investment, coordination, and control.”

May combine two claims.

BDA technology capability (BDATEC) was identified as a key predictor of BDAC, emphasizing the need for versatility of the analytics platform.

“BDA technology capability (BDATEC) was identified as a key predictor of BDAC, emphasizing the need for versatility of the analytics platform so that it connects data from various functions across the firm, ensures information flow, and develops robust models.”

May combine two claims.

Control variables (COVA) have an insignificant impact on FPER, as the R2 change is very small after including COVA.

“Similarly, we investigated the impact of control variables (COVA) on FPER, however, the results show insignificant impact of COVA as the R 2 change is very small after including this construct in the model.”

May combine two claims.

The size of the moderating effect is medium (f2 = 0.23) but significant at p < 0.05.

“According to the guidelines of Cohen (1988), the size of the moderating effect is medium (f 2 =0.23) but significant at p<0.05.”

• cites Cohen, 1988Not checked yet

  Not checked in the free run.

May combine two claims.

The degree of variance of the third-order BDAC construct explained by its second-order antecedents is 88% for BDAMAC, 83% for BDATEC, and 90% for BDATLC.

“The degree of variance of the third-order BDAC construct was explained by its second-order antecedents, that is, BDAMAC (88%), BDATEC (83%), and BDATLC (90%).”

May combine two claims. The quote only partly states this claim.

The higher-order BDAC has a positive significant impact on FPER, with a standardized beta of 0.709 in the main model, explaining 50% of the variance.

“The results provide a standardized beta of 0.709 for the BDAC-FPER path in the main, thus supporting H1.”

• Also stated in: § 6 Discussion · boosted

  “Overall, the findings of the structural model confirm that BDAC is a significant predictor of FPER (explaining 50% of the variance).”

• AssumptionRests on an assumption: The observed associations between BDAC, ACBSA and FPER reflect causal effects rather than mere association.

May combine two claims.

The degree of explained variance of BDAMAC was explained by BDAPL (82%), BDAID (79%), BDACO (72%), and BDACT (85%).

“For example, the degree of explained variance of BDAMAC was explained by BDAPL (82%), BDAID (79%), BDACO (72%), and BDACT (85%).”

May combine two claims.

BDAC was found to have a positive association with all primary dimensions, with BDA talent capability (BDATLC) emerging as the strongest.

“Big data analytics capability (BDAC) was found to have a positive association with all the primary dimensions with BDA talent capability (BDATLC) emerging as the strongest.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The empirical findings of our study are consistent with the conceptual findings of Kiron et al. (2014) that an effective analytics culture is built on more advanced data management processes, technologies and talent.

“The empirical findings of our study answer this question, and are consistent with the conceptual findings ofKiron et al. (2014, p.10) who state that”

• cites Kiron et al., 2014Not checked yet

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May combine two claims.

BDAC is a hierarchical construct having a strong influence on firm performance (FPER).

“Secondly, despite the paucity of empirical modeling in big data research, our research extends this stream by conceptualizing a multidimensional BDAC model drawing on the RBT and sociomaterialism which substantiate the fact that BDAC is a hierarchical construct having a strong influence on firm performance (FPER).”

Classified as probably not a substantial claim.

The empirical findings of our study answer the question of what capabilities (technical and nontechnical) an organization should acquire to succeed in big data efforts.

“The findings therefore contribute to answering”

Classified as probably not a substantial claim.

Based on resource-based theory, some scholars propose that internal business processes could be important factors linking BDAC and firm performance.

“Based on the RBT, some scholars propose that internal business processes could be important factors linking BDAC and firm performance (FPER) (Dehning and Richardson, 2002;Melville et al., 2004).”

• cites Dehning and Richardson, 2002Not checked yet

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• cites Melville et al., 2004Not checked yet

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Probably not a substantial claim: may not pass S4 (based).

Greater synchronization in the big data environment makes it possible to leverage BDAC by overcoming cognitive, structural and political challenges.

“As a result of greater synchronization in the big data environment, it is possible to leverage BDAC by overcoming cognitive, structural and political challenges.”

Probably not a substantial claim: may not pass S2 (checkable).

The organizational, physical, and human dimensions of BDAC are so interwoven that it is difficult to measure their individual contributions in isolation.

“Rather, the study embraces the relational ontology of sociomaterialism which posits that the organizational (i.e., BDA management), physical (i.e., IT infrastructure), and human (e.g., analytics skill or knowledge) dimensions are so interwoven that it is difficult to measure their individual contributions in isolation (Orlikowski and Scott, 2008).”

• cites Orlikowski and Scott, 2008 sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Capabilities represent a special type of resources whose objective is to increase productivity of other resources possessed by the firm.

“Overall, capabilities represent a special type of resources whose objective is to increase productivity of other resources possessed by the firm (Morgan et al., 2009).”

• cites Morgan et al., 2009Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The VRIO framework states that firm performance depends on the extent to which a firm possesses simultaneously valuable, rare, imperfectly imitable resources which are properly organized.

“In addition to these two assumptions, the logic of RBT embraces the VRIO framework which clearly states that firm performance depends on the extent to which a firm possesses simultaneously valuable (V), rare (R), imperfectly imitable (I) resources which are properly organized (O) (Amit and Schoemaker, 1993;Barney et al., 2001).”

• cites Amit and Schoemaker, 1993 sourceNot checked yet

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• cites Barney et al., 2001Not checked yet

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Classified as probably not a substantial claim.

Compatibility enables continuous flows of information for real-time decisions.

“The second component, compatibility, enables continuous flows of information for real-time decisions.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Resource-based theory (RBT) assumes resource immobility: differences in resources are facilitated by the difficulty of exchanging resources across firms.

“Second, these differences in resources are facilitated by the difficulty of exchanging resources across firms.This assumption indicates resource immobility which highlights the fact that the synergistic benefits from various resources are sustained over time (Barney and Hesterly, 2012).”

• cites Barney and Hesterly, 2012Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Strategy researchers have emphasized establishing strategic fit or alignment, viewing the firm as a collection of resources interlinked by a specific governance structure.

“Due to the unpredictable nature of big data, strategy researchers have always emphasized establishing the strategic fit or alignment, viewing the firm as a collection of resources, interlinked by a specific governance structure (Peteraf, 1993).”

• cites Peteraf, 1993Not checked yet

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May combine two claims.

Modularity helps in tapping business opportunities and improving firm performance (FPER).

“It helps in tapping business opportunities and improving FPER.”

May combine two claims.

The IT capabilities literature recognizes that competence in leveraging IT-based resources is a source of competitive advantage and differentiates firm performance.

“Drawing on the RBT, the literature in IT capabilities recognizes that competence in leveraging IT-based resources is a source of competitive advantage and differentiates firm performance (Bharadwaj, 2000a;Piccoli and Ives, 2005).”

• cites Bharadwaj, 2000aNot checked yet

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• cites Piccoli and Ives, 2005Not checked yet

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May combine two claims.

Competence in mobilizing and deploying various BDAC resources differentiates firm performance and creates competitive advantage.

“Since IT is acknowledged as a critical component of BDAC, drawing on the IT capability literature, we argue that competence in mobilizing and deploying various BDAC resources differentiates firm performance (FPER) and creates competitive advantage (Piccoli and Ives, 2005).”

• cites Piccoli and Ives, 2005Not checked yet

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Classified as probably not a substantial claim.

Previous research highlights the importance of analytics capability-business strategy alignment (ACBSA) in the big data environment.

“Previous research also highlights the importance of analytics capability-business strategy alignment (ACBSA) in big data environment, which is defined as the extent to which analytics strategies are aligned with the overall business strategy of the organization (Agarwal and Dhar, 2014;McAfee and Brynjolfsson, 2012).”

• cites Agarwal and Dhar, 2014Not checked yet

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• cites McAfee and Brynjolfsson, 2012Not checked yet

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Classified as probably not a substantial claim.

The flexibility of a firm's BDAC depends on connectivity among different business units in sourcing and analyzing a variety of data from different functions.

“Thus, the flexibility of a firm's BDAC depends on two components: the first component is connectivity among different business units in sourcing and analyzing a variety of data from different functions (e.g., supply chain management, customer relationship management, etc.).”

Classified as probably not a substantial claim.

Resource-based theory (RBT) assumes resource heterogeneity: even when firms operate within the same industry, they possess a varied mixture of resources.

“First, even when firms operate within the same industry, they possess a varied mixture of resources (Peteraf and Barney, 2003).This assumption of resource heterogeneity indicates the capability of some firms in accomplishing certain functions with the help of their unique resources.”

• cites Peteraf and Barney, 2003 sourceNot checked yet

  Not checked in the free run.

May combine two claims.

Firm performance in a data economy is enhanced only when capabilities are valuable, rare, imperfectly imitable and when the firm's organization or management exploits the potential of resources.

“Thus we present RBT to argue that firm performance in a data economy is enhanced only when capabilities are valuable, rare, imperfectly imitable and when the firm's organization or management exploits the potential of resources.”

May combine two claims.

A larger amount of synchronization between BDAC and business strategies increases synergy among functional units and positively impacts FPER.

“A larger amount of synchronization between BDAC and business strategies increases the synergy among different functional units and positively impacts FPER.”

May combine two claims.

BDAC dimensions are constitutively entangled and mutually supportive.

“This view also posits that no properties are native to each constituent dimension because BDAC dimensions are constitutively entangled (Orlikowski, 2007) and mutually supportive (Barton and Court, 2012).”

• cites Orlikowski, 2007 sourceNot checked yet

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• cites Barton and Court, 2012Not checked yet

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Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

The individual capability dimension is the manifestation of the overall BDAC building blocks as a whole.

“Indeed, the individual capability dimension is the manifestation of the overall BDAC building blocks as a whole.”

Classified as probably not a substantial claim.

According to resource-based theory (RBT), the competency of a firm depends on its capabilities to effectively manage its critical resources (both human and other resources) to achieve firm performance.

“According to the RBT, the competency of a firm depends on its capabilities to effectively manage its critical resources (both human and other resources) to achieve firm performance (FPER) (Grant, 2002).”

• cites Grant, 2002Not checked yet

  Not checked in the free run.

Classified as probably not a substantial claim.

Wixom et al. (2013) show that BDAC can improve FPER by improving productivity in tangible and intangible benefits.

“Wixom et al. (2013) show that BDAC can improve FPER by improving productivity both in tangible (i.e., less paper reporting) and intangible (company reputation) benefits.”

• cites Wixom et al., 2013Not checked yet

  Not checked in the free run.

Classified as probably not a substantial claim.

Confirmatory factor analysis (CFA) was used to verify convergent and discriminant validity of the first-order measurement model.

“Confirmatory factor analysis (CFA) was used to verify the convergent and discriminant validity of the first-order measurement model (Table 8).”

May combine two claims.

The study confirmed that all item loadings and CR and AVE values exceed cut-off values, ensuring adequate reliability and convergent validity.

“Thus, the study confirmed that all the item loadings and values for CR and AVE exceed their respective cut-off values, thus ensuring adequate reliability and convergent validity (Fornell and Larcker, 1981).”

• cites Fornell and Larcker, 1981 sourceNot checked yet

  Not checked in the free run.

May combine two claims.

Composite reliability (CR) and average variance extracted (AVE) of all scales are either equal to or exceed 0.80 and 0.50 cut-off values, respectively.

“Composite reliability (CR) and AVE of all scales are either equal to or exceed 0.80 and 0.50 cut-off values, respectively (Fornell and Larcker, 1981;Hair et al., 2013).”

• cites Fornell and Larcker, 1981 sourceNot checked yet

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• cites Hair et al., 2013Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Eight experienced analytics academics conducted content validity of the survey.

“Subsequently, eight experienced analytics academics conducted the content validity of the survey.”

May combine two claims.

BDAC is an important enabler of improved FPER, confirming the relationship between high-level BDAC and FPER.

“Firstly, our study suggests that BDAC is an important enabler of improved FPER, thus confirming the relationship between high-level BDAC and firm performance (FPER).”

May combine two claims.

The path coefficient of BDAC*ACBSA-FPER is significant, independently of BDAC-FPER and ACBSA-FPER relationships in the interaction model, confirming the significance of the moderator.

“We confirm the significance of the moderator because the path coefficient of the BDAC*ACBSA-FPER is significant, independently of BDAC-FPER and ACBSA-FPER relationships in the interaction model (Henseler and Fassott, 2010).”

• cites Henseler and Fassott, 2010Not checked yet

  Not checked in the free run.

May combine two claims.

The lowest AVE is 0.600 for BDA technology and the lowest CR is 0.902 for BDA connectivity; all exceed recommended thresholds.

“Here, the lowest AVE is 0.600 for BDA technology and the lowest CR is 0.902 for BDA connectivity: all of these values exceed the recommended thresholds.”

Probably not a substantial claim: may not pass S3 (load-bearing).

All measurement items were taken from existing literature and adapted to fit the big data analytics context.

“For this study, all measurement items were taken from the existing literature and were adapted to fit the big data analytics context (Appendix 1).”

Probably not a substantial claim: may not pass S3 (load-bearing).

The study controlled for demographic variables (age, gender, education, experience, industry, organization size) to avoid bias due to demographics.

“We controlled for the demographic variables relevant to the analytics managers such as, age, gender, education, experience, industry and the size of organization to avoid any bias due to demographics.”

May combine two claims.

All item loadings exceeded 0.7 and were significant at p < 0.001.

“Initially, the study calculated all the item loadings which exceeded the cut-off values of 0.7 and were significant at p < 0.001.”

Probably not a substantial claim: may not pass S2 (checkable).

The findings help minimize confusions regarding the role of strategic alignment in the RBT framework.

“Overall, the findings of the study help to minimize confusions regarding the role of strategic alignment in the RBT framework (Teece, 2014).”

• cites Teece, 2014Not checked yet

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Classified as probably not a substantial claim.

Nonparametric bootstrapping with 5,000 replications was applied to obtain standard errors of the estimates.

“The study applied nonparametric bootstrapping (Chin, 1998a;Efron and Tibshirani, 1993;Tenenhaus et al., 2005) with 5,000 replications to obtain the standard errors of the estimates (Hair Jr et al., 2013).”

• cites Chin, 1998aNot checked yet

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• cites Efron and Tibshirani, 1993Not checked yet

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• cites Tenenhaus et al., 2005 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

A recent big data study found that 87% of respondents suggest focusing on elevating their organizations to the next level of analytics management.

“A recent big data study (involving 2,037 professionals and interviews with more than 30 executives in 100 countries and 25 industries) reflects the importance of analytics management as 87% of its respondents suggest focusing on elevating their organizations to the next level of analytics management (Kiron et al., 2014).”

• cites Kiron et al., 2014Not checked yet

  Not checked in the free run.

May combine two claims.

ACBSA is a significant moderator or necessary condition for strong firm performance.

“These findings confirm ACBSA as the significant moderator or the necessary condition for strong firm performance (FPER).”

May combine two claims.

The estimated power (0.99) exceeds the cut-off value of 0.80, confirming that the associations are truly significant.

“The size of estimated power (0.99) compellingly exceeds the cut-off value of 0.80 (Cohen, 1992), confirming that the associations are truly significant.”

• cites Cohen, 1992 sourceNot checked yet

  Not checked in the free run.

May combine two claims.

The findings confirm the impact of BDAC and ACBSA on FPER, ensuring nomological validity of the overall research model.

“The findings of the study confirm the impact of BDAC and ACBSA on FPER, thereby ensuring the nomological validity of the overall research model.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

A pilot study of the survey was conducted with 61 respondents from big data analytics groups on LinkedIn, allowing the model to be tested for robustness before final data collection.

“A pilot study of the survey was then conducted with a total of 61 respondents enrolled from various big data analytics groups on LinkedIn.This allowed our proposed model to be tested for robustness before the final data collection.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

PLS path modeling ensures more theoretical parsimony and less model complexity.

“The study estimates the model using partial least squares (PLS) path modeling which is able to ensure more theoretical parsimony and less model complexity (Wetzels et al., 2009).”

• cites Wetzels et al., 2009 sourceNot checked yet

  Not checked in the free run.

May combine two claims.

Each item loads more on its own construct than on other constructs, and all constructs share substantial variance with their own items.

“In other words, each item loads more on its own construct than on other constructs and, therefore, all constructs share a substantial amount of variance with their own items (Chin, 1998b;Fornell and Bookstein, 1982).”

• cites Chin, 1998bNot checked yet

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• cites Fornell and Bookstein, 1982Not checked yet

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Classified as probably not a substantial claim. May combine two claims.

An invitation was sent to a random sample of 826 people using big data in the USA; 668 agreed; 152 valid questionnaires were analyzed, giving a response rate of 37.72%.

“To be more precise, an invitation to participate in the study was sent on to a random sample of 826 people who were using big data in the USA and who were members of the 'business analysts', 'big data analytics', and 'IT professionals' groups.A total of 668 panel members agreed to participate in the study.After a careful analysis of all responses, 152 valid questionnaires were considered to have”

• AssumptionRests on an assumption: The 152 valid questionnaires are representative of the population of big data-using firms in the USA, allowing generalization.

Classified as probably not a substantial claim. May combine two claims.

Improving BDAC and aligning strategy could help managers create new products and services (70%).

“For example, by improving BDAC and aligning strategy, managers could better serve customer needs (79%); increase sales and revenue (76%); create new products and services (70%); and expand into new markets (72%), with the help of quality information and robust insights (Columbus, 2014b).”

• cites Columbus, 2014bNot checked yet

  Not checked in the free run.

Classified as probably not a substantial claim. May combine two claims.

Improving BDAC and aligning strategy could help managers better serve customer needs (79%).

“For example, by improving BDAC and aligning strategy, managers could better serve customer needs (79%); increase sales and revenue (76%); create new products and services (70%); and expand into new markets (72%), with the help of quality information and robust insights (Columbus, 2014b).”

• cites Columbus, 2014bNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

Few scholars disagree with the inclusion of BDA management capability, BDA infrastructure capability, and BDA talent capability as key dimensions of BDAC.

“Therefore, one notable observation is that few scholars disagree with the inclusion of BDA management capability, BDA infrastructure capability, and BDA talent capability as key dimensions of BDAC.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The study's scope was limited to exploring BDAC dimensions and modeling the impact of BDAC on FPER with ACBSA as a moderator.

“its scope was limited to exploring BDAC dimensions and modeling the impact of BDAC on FPER with ACBSA as a moderator.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The study does not evaluate unobserved heterogeneity in the structural equation model (SEM).

“the study does not evaluate unobserved heterogeneity in the structural equation model (SEM).”

Probably not a substantial claim: may not pass S3 (load-bearing).

The taxonomy schemes proposed by the literature are similar as they reflect BDA management capability, BDA infrastructure capability and BDA talent capability-related aspects.

“Although BDAC dimensions differ in their terminology, the taxonomy schemes proposed by the literature are similar as they reflect BDA management capability, BDA infrastructure capability and BDA talent capability-related aspects.”

Probably not a substantial claim: may not pass S2 (checkable).

The study leads to a better understanding of capability-strategy-performance in data economy.

“Overall, the study leads to a better understanding of capability-strategy-performance in data economy and is likely to open new avenues of research into academic and corporate policy and practices.”

Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

Applying RBT and sociomaterialism in conceptualizing BDAC within the big data environment proves its utility in portraying the entanglement phenomenon in BDAC dynamics.

“Thirdly, by applying the RBT and the sociomaterialism perspective in conceptualizing BDAC within the big data environment, our research proves its utility in portraying the entanglement phenomenon in BDAC dynamics.”

Classified as probably not a substantial claim.

Our research addresses the challenge of proving the significance of BDAC as a source of firm performance by presenting the third-order BDAC model to capture variations in FPER.

“Our research specifically addresses this challenge by presenting the third-order BDAC model to capture the variations in firm performance (FPER).”

• AssumptionRests on an assumption: The emerging BDA research has been struggling to encapsulate and prove the significance of BDAC as a source of firm performance.

Probably not a substantial claim: may not pass S2 (checkable).

This research builds a theory of BDAC strategy that shows how to leverage the BDAC dimensions and sub-dimensions in order to build an overall BDAC climate.

“This research builds a theory of BDAC strategy that shows how to leverage the BDAC dimensions and sub-dimensions in order to build an overall BDAC climate.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

There is a growing focus on the BDAC-ACBSA-FPER link in the BDA environment across various industries.

“Consequently, there is a growing focus on the BDAC-ACBSA-FPER link in the BDA environment across various industries.”

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Our work illuminates the role of RBT and entanglement view in proposing an integrated BDAC model and its overall impact on firm performance.

“Although several studies highlight the importance of management, technology and talent capability in big data environment, our work illuminates the role of RBT and entanglement view in proposing an integrated BDAC model and its overall impact on firm performance.”

Probably not a substantial claim: may not pass S4 (based). May combine two claims.

This research applies RBT as a unifying paradigm for combining other theories (e.g., sociomaterialism and IT capability) and presents a parsimonious foundation for multiple theoretical perspectives.

“This research applies RBT as a unifying paradigm for combining other theories (e.g., sociomaterialism and IT capability) and presents a parsimonious foundation for multiple theoretical perspectives.”

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

The current study advances BDAC conceptualization and the role of ACBSA in enhancing FPER.

“With the growing interests in business analytics across various industries, the current study advances BDAC conceptualization and the role of ACBSA in enhancing FPER.”

Classified as probably not a substantial claim.

Data were collected from multiple industries to empirically test the model.

“A notable strength of the current study is that data were collected from multiple industries to empirically test the model.”

Probably not a substantial claim: may not pass S3 (load-bearing).

This study used a 7-point Likert scale to measure all the items, which may introduce acquiescence bias.

“this study used a 7-point Likert scale to measure all the items, which may introduce the so-called 'acquiescence bias' (Chin et al., 2008).”

• cites Chin et al., 2008Not checked yet

  Not checked in the free run.

Classified as probably not a substantial claim. May combine two claims.

Improving BDAC and aligning strategy could help managers increase sales and revenue (76%).

“For example, by improving BDAC and aligning strategy, managers could better serve customer needs (79%); increase sales and revenue (76%); create new products and services (70%); and expand into new markets (72%), with the help of quality information and robust insights (Columbus, 2014b).”

• cites Columbus, 2014bNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Improving BDAC and aligning strategy could help managers expand into new markets (72%).

“For example, by improving BDAC and aligning strategy, managers could better serve customer needs (79%); increase sales and revenue (76%); create new products and services (70%); and expand into new markets (72%), with the help of quality information and robust insights (Columbus, 2014b).”

• cites Columbus, 2014bNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

Certain issues (e.g., the analytics climate, privacy, surveillance and democracy) could not be encapsulated into this study.

“certain burning issues (e.g., the analytics climate, privacy, surveillance and democracy) could not be encapsulated into this study but might be investigated in future research.”

May combine two claims.

The findings emphasize not only the importance of BDAC development but also a strong alignment between BDAC and ACBSA in order to achieve improved FPER.

“Secondly, the findings of our study emphasize not only the importance of BDAC development but also a strong alignment between BDAC and ACBSA in order to achieve improved firm performance (FPER).”

Classified as probably not a substantial claim.

Our research extends the stream of empirical modeling in big data research by conceptualizing a multidimensional BDAC model drawing on RBT and sociomaterialism.

“Secondly, despite the paucity of empirical modeling in big data research, our research extends this stream by conceptualizing a multidimensional BDAC model drawing on the RBT and sociomaterialism which substantiate the fact that BDAC is a hierarchical construct having a strong influence on firm performance (FPER).”

• AssumptionRests on an assumption: There is a paucity of empirical modeling in big data research.