Social Media as a Strategic Tool: Going Beyond the Obvious

Bakar

2019

IJEBR

247

215

Purpose Through social media technologies, small and medium-sized enterprises (SMEs) can communicate information and respond to competitors with minimal cost. The ability to share and access information can affect SMEs’ performance, but there is little research on the link between SMEs’ social media adoption and their performance. The purpose of this paper is to present a quantitative survey to explore factors that influenced social media adoption by SMEs in the United Arab Emirates (UAE), and its impact on performance. Design/methodology/approach The study used a multi-perspective framework combining technological, organizational and environmental elements affecting SMEs. Survey questionnaires were used to collect data from a random sample of SMEs operating in the UAE. Using partial least squares and structural equation modeling techniques, 144 responses were analyzed. Findings Social media adoption had no effect on SMEs’ performance. These findings could help managers and decision makers in the SME sector to try to keep pace with research on social media innovations, and enable them to benefit from social commerce as it becomes more ubiquitous. Research limitations/implications This has implications for social media experts and anyone wishing to encourage social media use by SMEs. Originality/value The study developed a suitable multi-perspective framework covering various factors that may affect social media use. It also tested the framework empirically on a sample of SMEs from the UAE.

Section: Introductionmentioning

confidence: 99%

Social media adoption and its impact on firm performance: the case of the UAE

Bakar

2019

IJEBR

247

215

Journal of Cases on Information Technology

“…Standard execution of internet based applications in management education is vital for improving learning impediments. By surveying over 400 management students at the various Universities in the India, Arora & Predmore (2013) uncovered that internet based applications enhance students' learning and work execution after graduation and, that enhanced technological effectiveness is the essential driver of these enhancements. Moreover, researcher demonstrated that internet based applications are progressively helpful for communication and content generation purposes than for learning and educating purposes.…”

Section: Literature Reviewmentioning

confidence: 99%

Attitude Towards the Usage of Internet-Based Applications in Management Education

Bhandari

Bansal

2021

Internet based applications are as a tool progressively used to encourage learning and relationship management in management education. This examination analyzed the attitude of students and educators towards utilizing internet based applications in the management education. Following the literature review that presented 11 internet based applications utilized in classroom settings, questionnaires were distributed to students and educators from three state funded management institutes in Delhi. Responses of 341 management students and 46 faculty members with respect to 5 domains of internet based applications – feedback, classroom management, content creation and publication, communication, and social media – were broke down to explore the attitude towards utilization of internet based applications. The outcomes uncovered that students apparent the internet based applications of communication and social media to be useful in learning and in expanding their future skills; likewise, the educators observed these internet based applications to be valuable.

“…Lastly, still in the context of collaboration and knowledge sharing inside and outside the organisation, there are several contributions belonging to this cluster that focus on the opportunities offered by Web 2.0 tools. For instance, Arora and Predmore (2013) claim that social networks enable the creation of an open and transparent corporate environment, where anyone can intervene to propose innovative ideas (concerning products and business processes). Such ideas are then selected and implemented by the organisation (i.e.…”

Section: Green Cluster: Big Data and Knowledge Managementmentioning

confidence: 99%

“…Big data to support supply chain strategyBrinch (2018);Handfield et al (2019); Nguyen Dang Tuan et al(2019);Wang et al (2016) Big data to facilitate supplier and strategic partners collaborationNagy et al (2018);Navickas and Gružauskas (2016); G Wang et al (2016). Big data and supply chain agilityFosso Wamba, Dubey, et al (2019); Li and Wang (2017); Richey et al (2016); Roßmann et al (2018); Wang et al (2016) Big data and supply chain sustainability El-Kassar and Singh (2019); Gružauskas et al (2018); G. Wang et al (2016); Zhang et al (2018) Red cluster: Big data, personalisation and co-creation strategies Big data and segmentation, targeting and positioning strategies Ahani et al (2019); Kumar et al (2017); Quinn et al (2016); Taylor-West et al (2018) Big data and Open Innovation: 'user-centred' strategies Bendle and Wang (2016); Qi et al (2016); Trabucchi et al (2018) Big data and Open Innovation: 'user-driven' strategies Buhalis and Sinarta (2019); Kunz et al (2017); Trabucchi et al (2018); Xie et al (2016) Innovative strategies for the exploitation of big data Sorescu (2017); Trabucchi and Buganza (2019a, 2019b); Trabucchi et al (2017) Blue cluster: Big data, strategic planning and strategic value creation pathways Big data as a driver of strategic planning Constantiou and Kallinikos (2015); Gnizy (2019); Mazzei and Noble (2017); O'Connor and Kelly (2017) Value creation pathways enabled by big data Elia et al (2019); Grover et al (2018); Y. Wang et al (2018) Big data and strategic value creation paths from a Resource-Based View perspective Cheah and Wang (2017); Grover et al (2018); Roden et al (2017) Big data and strategic value creation paths from a Dynamic Capabilities perspective Côrte-Real et al (2017, 2019); Grover et al (2018); Prescott (2014) Big data and strategic value creation paths from a strategic alignment theory perspective Akter et al (2016); Grover et al (2018) Green cluster: Big data and knowledge management Influence of big data on knowledge management strategies Harlow (2018); Intezari and Gressel (2017); Landaeta Olivo et al (2016); Tian (2017) Big data and decision support systems Aversa et al (2018); Festa et al (2018); Osuszek et al (2016) Big data for the development of collaborative knowledge networks Buhalis and Leung(2018);Del Vecchio, Di Minin, et al, (2018);Romanelli (2018);Troisi et al (2018) Big data and knowledge sharing using Web 2.0Arora and Predmore (2013);Del Vecchio, Mele, et al (2018);Richard (2017) …”

mentioning

confidence: 99%

The big data-business strategy interconnection: a grand challenge for knowledge management. A review and future perspectives

Ciampi

Marzi

Demi

et al. 2020

JKM

Purpose Designing knowledge management (KM) systems capable of transforming big data into information characterised by strategic value is a major challenge faced nowadays by firms in almost all industries. However, in the managerial field, big data is now mainly used to support operational activities while its strategic potential is still largely unexploited. Based on these considerations, this study proposes an overview of the literature regarding the relationship between big data and business strategy. Design/methodology/approach A bibliographic coupling method is applied over a dataset of 128 peer-reviewed articles, published from 2013 (first year when articles regarding the big data-business strategy relationship were published) to 2019. Thereafter, a systematic literature review is presented on 116 papers, which were found to be interconnected based on the VOSviewer algorithm. Findings This study discovers the existence of four thematic clusters. Three of the clusters relate to the following topics: big data and supply chain strategy; big data, personalisation and co-creation strategies and big data, strategic planning and strategic value creation. The fourth cluster concerns the relationship between big data and KM and represents a ‘bridge’ between the other three clusters. Research limitations/implications Based on the bibliometric analysis and the systematic literature review, this study identifies relevant understudied topics and research gaps, which are suggested as future research directions. Originality/value This is the first study to systematise and discuss the literature concerning the relationship between big data and firm strategy.