Abstract:PurposeThe purpose of this paper is to present a novel framework for strategic decision making using Big Data Analytics (BDA) methodology.Design/methodology/approachIn this study, two different machine learning algorithms, Random Forest (RF) and Artificial Neural Networks (ANN) are employed to forecast export volumes using an extensive amount of open trade data. The forecasted values are included in the Boston Consulting Group (BCG) Matrix to conduct strategic market analysis.FindingsThe proposed methodology i… Show more
“…Despite the rapid growth of digital technologies, they stated that industries also face particular challenges in the adoption and effective use of digital technologies, particularly in the case of productivity-enhancing applications. Furthermore, digital technology creates new growth opportunities for businesses and aids them in making strategic decisions that increase their productivity [86]. Similar findings have been discovered by Ellis et al [58], who pointed out that the digital technology such as IoT and cloud computing can capture vital data in analytics to drive end-to-end supply chain improvements.…”
In this rapidly developing digital era, digital transformations take place within every industry, and they have effects on the management of the supply chains. The aim of this study is to delve into the influence of the digital supply chain on the quality, productivity, and cost reduction aspects of operational performance. This study relies on quantitative methodology and data collected from the food and beverage industry of Indonesia. Data from a survey comprising a total of 209 responses were selected for investigation. PLS-SEM was used to perform the analysis. The investigation reveals that the digital supply chain has significant effects on operational performance in terms of quality, productivity, and cost reduction performance. This study contributes to the understanding of supply chain management by addressing the knowledge gap associated with the digital supply chain. In particular, it has concentrated on the hitherto unresearched effect of operational performance in the context of the Indonesian manufacturing industry.
“…Despite the rapid growth of digital technologies, they stated that industries also face particular challenges in the adoption and effective use of digital technologies, particularly in the case of productivity-enhancing applications. Furthermore, digital technology creates new growth opportunities for businesses and aids them in making strategic decisions that increase their productivity [86]. Similar findings have been discovered by Ellis et al [58], who pointed out that the digital technology such as IoT and cloud computing can capture vital data in analytics to drive end-to-end supply chain improvements.…”
In this rapidly developing digital era, digital transformations take place within every industry, and they have effects on the management of the supply chains. The aim of this study is to delve into the influence of the digital supply chain on the quality, productivity, and cost reduction aspects of operational performance. This study relies on quantitative methodology and data collected from the food and beverage industry of Indonesia. Data from a survey comprising a total of 209 responses were selected for investigation. PLS-SEM was used to perform the analysis. The investigation reveals that the digital supply chain has significant effects on operational performance in terms of quality, productivity, and cost reduction performance. This study contributes to the understanding of supply chain management by addressing the knowledge gap associated with the digital supply chain. In particular, it has concentrated on the hitherto unresearched effect of operational performance in the context of the Indonesian manufacturing industry.
“…This study reported that BDU is not directly linked to SCP and SMEs' performance, which is not consistent with the research work of 1 Özemre and Kabadurmus (2020), Mangla et al (2020), Raguseo (2018) and Akter et al (2016). Özemre and Kabadurmus (2020) highlighted that big data adoption brings new growth opportunities for firms and assist them in strategic decision-making to improve their productivity.…”
Section: Discussioncontrasting
confidence: 63%
“…This study reported that BDU is not directly linked to SCP and SMEs' performance, which is not consistent with the research work of 1 Özemre and Kabadurmus (2020), Mangla et al (2020), Raguseo (2018) and Akter et al (2016). Özemre and Kabadurmus (2020) highlighted that big data adoption brings new growth opportunities for firms and assist them in strategic decision-making to improve their productivity. Similarly, Mangla et al (2020) mentioned that big data adoption is positively linked to project performance of manufacturing organizations, while Raguseo (2018) investigated the relationship between the adoption of big data technologies, risk, benefits and firm performance and found that big data technologies have a positive effect on FP.…”
PurposeThis paper aims to investigate the use of big data (BDU) in predicting technological innovation, supply chain and SMEs' performance and whether technological innovation mediates the association between BDU and firm performance. Additionally, this research also seeks to explore the moderating effect of information sharing in the association between BDU and technological innovation.Design/methodology/approachUsing survey methods and structural associations in AMOS 24.0., the proposed model was tested on SME managers recruited from the largest economic and manufacturing hub of China, Pearl River Delta.FindingsThe findings suggest that BDU is positively related to technological innovation (product and process) and organizational outcomes (e.g., supply chain and SMEs performance). Technological innovation (i.e., product and process) significantly mediates the association between BDU and organizational outcomes. Moreover, information sharing positively moderates the association between BDU and technological innovations.Practical implicationsThis research provides deeper insights into how BDU is useful for SME managers in achieving the firm’s goals. Particularly, SME managers can bring technological innovation into their business processes, overcome the challenges of forecasting, and generate dynamic capabilities for attaining the best SMEs’ performance. Additionally, BDU with information sharing enables SMEs reduce their risk and decrease production costs in their manufacturing process.Originality/valueFirms always need to adopt new ways to enhance their productivity using available resources. This is the first study that contributes to big data and performance management literature by exploring the moderating and mediation mechanism of information sharing and technological innovation respectively using RBVT. The study and research model enhances our insights on BDU, information sharing, and technological innovation as valuable resources for organizations to improve supply chain performance, which subsequently increases SME productivity. This gap was overlooked by previous researchers in the domain of big data.
“…The global market for Big Data estimated at US$70.5 Billion in the year 2020, is projected to reach a revised size of US$243.4 Billion by 2027, growing at a CAGR of 19.4% over the analysis period 2020-2027. (Research and Markets, 2021) In an increasingly borderless global economy, big data plays a crucial role to successfully reap business and marketing opportunities (Chierici et al, 2019;Del Vecchio et al, 2020;Doh et al, 2016;Gnizy, 2019;€ Ozemre and Kabadurmus, 2020;Shamim et al, 2020). It has been witnessed that 91.6% of Fortune 1,000 companies invested in big data associated mechanisms as this investment is required to stay both agile and competitive in the market place (Osborne, 2019).…”
PurposeBig data is one of the most demanding topics in contemporary marketing research. Despite its importance, the big data-based strategic orientation in international marketing is yet to be formed conceptually. Thus, the purpose of this study is to systematically review and propose a holistic framework on big data-based strategic orientation for firms in international markets to attain a sustained firm performance.Design/methodology/approachThe study employed a systematic literature review to synthesize research rigorously. Initially, 2,242 articles were identified from the selective databases, and 45 papers were finally reported as most relevant to propose an integrative conceptual framework.FindingsThe findings of the systematic literature review revealed data-evolving, and data-driven strategic orientations are essential for performing international marketing activities that contain three primary orientations such as (1) international digital platform orientation, (2) international market orientation and (3) international innovation and entrepreneurial orientation. Eleven distinct sub-dimensions reflect these three primary orientations. These strategic orientations of international firms may lead to advanced analytics orientation to attain sustained firm performance by generating and capturing value from the marketplace.Research limitations/implicationsThe study minimizes the literature gap by forming knowledge on big data-based strategic orientation and framing a multidimensional framework for guiding managers in the context of strategic orientation for international business and international marketing activities. The current study was conducted by following only a systematic literature review exclusively in firms' overall big data-based strategic orientation concept in international marketing. Future research may extend the domain by introducing firms' category wise systematic literature review.Originality/valueThe study has proposed a holistic conceptual framework for big data-driven strategic orientation in international marketing literature through a systematic review for the first time. It has also illuminated a future research agenda that raises questions for the scholars to develop or extend theory in this area or other related disciplines.
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