Do tweets create value? A multi-period analysis of Twitter use and content of tweets for manufacturing firms

Majumdar, Adrija; Bose, Indranil

doi:10.1016/j.ijpe.2019.04.008

Cited by 51 publications

(27 citation statements)

References 34 publications

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“…Therefore, we contribute to the research on effective customer involvement to create synergies and networks that are necessary for the creation of products that satisfy customer needs and aspirations and the strategic goals of the organisation (Romero and Molina 2011; Niesten and Stefan 2019). By analysing Twitter data, we illustrate the usefulness of social media in the co-creation process as a sense-making device that assists managers and developers to make sense of the data available (Lycett 2013;Wei et al 2014) and customer sentiment and decision-making opportunities (Duan et al 2019;Dwivedi et al 2019) throughout the whole NPD process (Zhan et al 2018;Du et al 2016;Fuchs and Schreier 2011;Majumdar and Bose 2019). Therefore, we argue that the NPD is inseparable from the familiarity with the law of market operation and the understanding of customer needs.…”

Section: Implications For Researchmentioning

confidence: 99%

“…In the era of Big Data, Analytical processes and AI, the traditional decision-making process has not kept up with the times; as the evolution of technology provides cheaper and faster decision-making solutions as data are evolving and increasing in volume and formats (Bawack et al 2019;Feki et al 2016;Fosso Wamba et al 2017;Queiroz and Telles 2018;, the NPD process should also focus on "making sense" of the data available (Lycett 2013;Wei et al 2014). The sensemaking process of public views for NPD can utilise feedback and comments from social media and highlight the iterative role of the customer in value co-creation while exploring the sentiment throughout the whole NPD process (Zhan et al 2018;Du et al 2016;Fuchs and Schreier 2011;Majumdar and Bose 2019).…”

Section: Introductionmentioning

confidence: 99%

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Social media and sensemaking patterns in new product development: demystifying the customer sentiment

et al. 2020

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Artificial intelligence by principle is developed to assist but also support decision making processes. In our study, we explore how information retrieved from social media can assist decision-making processes for new product development (NPD). We focus on consumers' emotions that are expressed through social media and analyse the variations of their sentiments in all the stages of NPD. We collect data from Twitter that reveal consumers' appreciation of aspects of the design of a newly launched model of an innovative automotive company. We adopt the sensemaking approach coupled with the use of fuzzy logic for text mining. This combinatory methodological approach enables us to retrieve consensus from the data and to explore the variations of sentiments of the customers about the product and define the polarity of these emotions for each of the NPD stages. The analysis identifies sensemaking patterns in Twitter data and explains the NPD process and the associated steps where the social interactions from customers can have an iterative role. We conclude the paper by outlining an agenda for future research in the NPD process and the role of the customer opinion through sensemaking mechanisms.

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Section: Implications For Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Social media and sensemaking patterns in new product development: demystifying the customer sentiment

et al. 2020

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“…For the other steps from those marked in Table 4 (i.e., Steps 1, 7 and 9), no application is reported in the scientific literature thus far, and, therefore, research opportunities are discovered. Note that four works in Table 5 are not shown in Table 6, as they were deemed not so relevant to the conceptual design of PSS: reference [94] improved the detailed design of production processes, reference [101] addressed sales operations, and references [97,102] addressed mainly firm-level activities.…”

Section: Discovering Research Opportunities In Pss Conceptual Design mentioning

confidence: 99%

A Product/Service System Design Schema: Application to Big Data Analytics

Sakao

Neramballi

2020

Sustainability

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The challenge of environmental sustainability has required product/service systems (PSSs) to play a substantial role. New technologies such as big data analytics (BDA), which have high potential to improve or enable PSSs, are increasingly implemented in industry. However, research achieved in the past and research opportunities in the intersection of PSS design and BDA are unclear in the literature. Therefore, this article took an inter-disciplinary approach and aimed to pave the way forward for research and development in PSS design and show opportunities to improve PSS design and delivery using BDA. The research methods adopted were literature synthesis and systematic literature review. The synthesis of PSS design literature resulted in a schema consisting of 10 design steps for PSS conceptual design. The systematic review of BDA literature found 11 research works, including industrial applications, which were then mapped on to the PSS design schema. This revealed the achievement of applied research using BDA for some of the PSS design steps as well as opportunities of research for the others. The two inter-related areas of research, PSS design and BDA, were connected with each other more clearly, so that further research could be anchored and motivated with more specificity.

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“…Sosial media yang memiliki fokus untuk diskusi topik adalah twitter. Pada kuartal pertama 2018 twitter memiliki 336 juta pengguna aktif [2]. Oleh sebab itu twitter merupakan indikator yang baik dalam penelitian Analisa sentimen [3].…”

Section: Pendahuluanunclassified

“…Akurasi merupakan nilai keberhasilan pengukuran dengan nilai sebernarnya (1). Presisi adalah nilai ketepatan antar informasi yang dicari dengan hasil pengukuran (2). Recall adalah tingkat keberhasilan pengukuran dalam menemukan kembali sebuah informasi (3).…”

Section: Skenario Pengujianunclassified

Analisa Sentimen Tweet Berbahasa Indonesia Dengan Menggunakan Metode Lexicon Pada Topik Perpindahan Ibu Kota Indonesia

fatra

Hayatin²,

Aditya³

2020

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This study proposes a classification of public response to the government's decision to move the Indonesian capital using the lexicon method. The results of testing accuracy are measured using a confusion matrix. The data in this study use data from Twitter in the form of tweets. The data contains tweets of community responses to the decision to move the Indonesian capital. Data passes through 5 preprocessing processes, namely case folding, punctuation removal, stopword removal, stemming, and tokenizing. Lexicon is used because it produces good accuracy values. In this study also will look for a dictionary that has the best classification results. The results of this study show the results of a good classification by approaching the results by experts.

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Do tweets create value? A multi-period analysis of Twitter use and content of tweets for manufacturing firms

Cited by 51 publications

References 34 publications

Social media and sensemaking patterns in new product development: demystifying the customer sentiment

Social media and sensemaking patterns in new product development: demystifying the customer sentiment

A Product/Service System Design Schema: Application to Big Data Analytics

Analisa Sentimen Tweet Berbahasa Indonesia Dengan Menggunakan Metode Lexicon Pada Topik Perpindahan Ibu Kota Indonesia

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