On realising the utopian potential of big data analytics for maximising return on marketing investments

Benoit, Dries F.; Lessmann, Stefan; Verbeke, Wouter

doi:10.1080/0267257x.2020.1739446

Cited by 23 publications

(6 citation statements)

References 48 publications

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“…The use of MA is the indication of a firm's market sensing capability. (Cao et al, 2019;Benoit et al, 2020). Alshanty and Emeagwali (2019) identifies market-sensing as a tool used by firms to develop themselves, through generation of market intelligence relating to current and future behavior of consumers.…”

Section: How Marketing Capabilities Are Enhanced By Marketing Analytics?mentioning

confidence: 99%

Operationalization of Marketing Capabilities in the Context of Analytics Technology Adoption

Silaban,

Lapian,

Tumbel

et al. 2023

IMJ

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<p>The advent of analytics has been considered as a revolution in how firms treat data. However, the implementation of this technology is still an issue for researchers and practitioners. Many business leaders still reluctant to adopt this technology since it is still unclear how analytics adds value on firms. There are limited studies that incorporate analytics and capabilities, particularly in marketing. Moreover, there is also lack of empirical studies that cover the adaptive side of marketing capabilities. This study aims to close the gap by constructing a sound and holistic measurement of firms’ marketing capabilities (MCs) to measure the impact of analytics-related adoption. Integrative literature review was carried out to synthesize previous MCs constructs. Then, analysis was conducted to develop a new construct of MCs measurement. The result of this study proposes a more detailed and comprehensive framework in understanding the impact of marketing analytics (MA) adoption on all dimensions of MCs, including adaptive side of MCs.</p>

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Section: How Marketing Capabilities Are Enhanced By Marketing Analytics?mentioning

confidence: 99%

Operationalization of Marketing Capabilities in the Context of Analytics Technology Adoption

Silaban,

Lapian,

Tumbel

et al. 2023

IMJ

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“…BD also contributes to organisational performance by aiding improvements in traditional value-chain activities, such as product development, distribution and customer service (Verma & Chaurasia, 2019). Worryingly, the expected value creation associated with the concept of BD may not necessarily crystallise due to poor application (Benoit, Lessmann & Verbeke, 2020) possibly stemming from a weak understanding of the essential antecedents of BDA. Sun et al, (2018) observe that monetary costs and organisational alignment with an innovative technology could impact on an organisation's decision to adopt BD.…”

Section: Empirical Review and Hypothesis Developmentmentioning

confidence: 99%

Antecedents of big data adoption in financial institutions

Eresia-Eke,

Mojalefa,

Nyanga

2023

IJRBS

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Big data (BD) adoption is still relatively slow despite the numerous business opportunities that it embodies. Within the context of financial institutions in South Africa, the specific drivers of big data adoption remain largely indeterminate. Consequently, this study explores the possible relationships between perceived usefulness and perceived ease of use and actual big data adoption, while being duly cognisant of the role that behavioural intention to adopt big data could play. The study employed a survey research approach and relied on data collected from a purposive sample of 195 management level employees of financial institutions. Regression analysis to test the hypothesised relationships in the study revealed that perceived usefulness and perceived ease of use were statistically significant predictors of big data adoption. Instructively, this relationship was subject to the extent of behavioural intention of respondents. For respondents with a low behavioural intention to adopt big data, perceived usefulness and perceived ease of use displayed a statistically insignificant relationship with big data adoption. Conversely, the regression model for the group of respondents with a high behavioural intention to adopt big data is statistically significant. These findings enrich literature related to big data from a developing country context while concurrently identifying veritable antecedents of big data adoption in financial institutions.

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“…with the help of data analysis. Benoit et al (2020) mention real cases in which companies created value and provided higher productivity with data analysis. Therefore, they apply data as a means of obtaining competitive advantage.…”

Section: Notesmentioning

confidence: 99%

Incorporating data quality into a multi-product procurement planning under risk

Shabani-Naeeni

Yaghin

2021

JBIM

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Purpose In the data-driven era, the quality of the data exchanged between suppliers and buyer can enhance the buyer’s ability to appropriately cope with the risks and uncertainties associated with raw material purchasing. This paper aims to address the issue of supplier selection and purchasing planning considering the quality of data by benefiting from suppliers’ synergistic effects. Design/methodology/approach An approach is proposed to measure data visibility’s total value using a multi-stage algorithm. A multi-objective mathematical optimization model is then developed to determine the optimal integrated purchasing plan in a multi-product setting under risk. The model contemplates three essential objective functions, i.e. maximizing total data quality and quantity level, minimizing purchasing risks and minimizing total costs. Findings With emerging competitive areas, in the presence of industry 4.0, internet of things and big data, high data quality can improve the process of supply chain decision-making. This paper supports the managers for the procurement planning of modern organizations under risk and thus provides an in-depth understanding for the enterprises having the readiness for industry 4.0 transformation. Originality/value Various data quality attributes are comprehensively subjected to deeper analysis. An applicable procedure is proposed to determine the total value of data quality and quantity required for supplier selection. Besides, a novel multi-objective optimization model is developed to determine the purchasing plan under risk.

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On realising the utopian potential of big data analytics for maximising return on marketing investments

Cited by 23 publications

References 48 publications

Operationalization of Marketing Capabilities in the Context of Analytics Technology Adoption

Operationalization of Marketing Capabilities in the Context of Analytics Technology Adoption

Antecedents of big data adoption in financial institutions

Incorporating data quality into a multi-product procurement planning under risk

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